{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\ks298\Dropbox\FairnessSurvey\Data\Replication\SS_CPS_2021_Replication.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}18 Jan 2021, 14:12:49
{txt}
{com}. 
. /**
> Historical Inquality Analysis: Tables 1-3
> **/
. 
. use inequalityanalysis.dta, clear
{txt}
{com}. 
. keep if year==1860|year==1865|year==1870|year==1875|year==1880|year==1885|year==1890|year==1895|year==1900|year==1905|year==1910|year==1915|year==1920|year==1925|year==1930|year==1935|year==1940|year==1945|year==1950|year==1955|year==1960|year==1965|year==1970|year==1975|year==1980|year==1985|year==1990|year==1995|year==2000|year==2005|year==2010 /*Keep only five-year intervals*/
{txt}(2,851 observations deleted)

{com}. 
. gen period=.
{txt}(554 missing values generated)

{com}. replace period=1 if year==1860
{txt}(12 real changes made)

{com}. replace period=2 if year==1865
{txt}(13 real changes made)

{com}. replace period=3 if year==1870
{txt}(14 real changes made)

{com}. replace period=4 if year==1875
{txt}(15 real changes made)

{com}. replace period=5 if year==1880
{txt}(15 real changes made)

{com}. replace period=6 if year==1885
{txt}(15 real changes made)

{com}. replace period=7 if year==1890
{txt}(15 real changes made)

{com}. replace period=8 if year==1895
{txt}(15 real changes made)

{com}. replace period=9 if year==1900
{txt}(15 real changes made)

{com}. replace period=10 if year==1905
{txt}(17 real changes made)

{com}. replace period=11 if year==1910
{txt}(17 real changes made)

{com}. replace period=12 if year==1915
{txt}(17 real changes made)

{com}. replace period=13 if year==1920
{txt}(18 real changes made)

{com}. replace period=14 if year==1925
{txt}(19 real changes made)

{com}. replace period=15 if year==1930
{txt}(19 real changes made)

{com}. replace period=16 if year==1935
{txt}(19 real changes made)

{com}. replace period=17 if year==1940
{txt}(19 real changes made)

{com}. replace period=18 if year==1945
{txt}(20 real changes made)

{com}. replace period=19 if year==1950
{txt}(20 real changes made)

{com}. replace period=20 if year==1955
{txt}(20 real changes made)

{com}. replace period=21 if year==1960
{txt}(20 real changes made)

{com}. replace period=22 if year==1965
{txt}(20 real changes made)

{com}. replace period=23 if year==1970
{txt}(20 real changes made)

{com}. replace period=24 if year==1975
{txt}(20 real changes made)

{com}. replace period=25 if year==1980
{txt}(20 real changes made)

{com}. replace period=26 if year==1985
{txt}(20 real changes made)

{com}. replace period=27 if year==1990
{txt}(20 real changes made)

{com}. replace period=28 if year==1995
{txt}(20 real changes made)

{com}. replace period=29 if year==2000
{txt}(20 real changes made)

{com}. replace period=30 if year==2005
{txt}(20 real changes made)

{com}. replace period=31 if year==2010
{txt}(20 real changes made)

{com}. 
. qby countryn: gen wealth_ipolate_lag = wealth_ipolate[_n-1]
{txt}
{com}. qby countryn: gen wealth_ipolate_lag2 = wealth_ipolate[_n-2]
{txt}
{com}. qby countryn: gen wealth_ipolate_lag3 = wealth_ipolate[_n-3]
{txt}
{com}. 
. qby countryn: gen top_inheritance_n_lag = top_inheritance_n[_n-1]  
{txt}
{com}. qby countryn: gen top_inheritance_n_lag2 = top_inheritance_n[_n-2]
{txt}
{com}. qby countryn: gen top_inheritance_n_lag3 = top_inheritance_n[_n-3]
{txt}
{com}. 
. qby countryn: gen top_incrate_nl_lag=top_incrate_nl[_n-1]
{txt}
{com}. qby countryn: gen top_incrate_nl_lag2=top_incrate_nl[_n-2]
{txt}
{com}. qby countryn: gen top_incrate_nl_lag3=top_incrate_nl[_n-3]
{txt}
{com}. 
. qby countryn: gen top_incrate_n_lag=top_incrate_n[_n-1]
{txt}
{com}. qby countryn: gen top_incrate_n_lag2=top_incrate_n[_n-2]
{txt}
{com}. qby countryn: gen top_incrate_n_lag3=top_incrate_n[_n-3]
{txt}
{com}. 
. qby countryn: gen Top1incomeshare_ipolate_lag=Top1incomeshare_ipolate[_n-1]
{txt}
{com}. qby countryn: gen Top1incomeshare_ipolate_lag2=Top1incomeshare_ipolate[_n-2]
{txt}
{com}. qby countryn: gen Top1incomeshare_ipolate_lag3=Top1incomeshare_ipolate[_n-3]
{txt}
{com}. 
. qby countryn: gen Top01incomeshare_ipolate_lag=Top01incomeshare_ipolate[_n-1]
{txt}
{com}. qby countryn: gen Top01incomeshare_ipolate_lag2=Top01incomeshare_ipolate[_n-2]
{txt}
{com}. qby countryn: gen Top01incomeshare_ipolate_lag3=Top01incomeshare_ipolate[_n-3]
{txt}
{com}. 
. qby countryn: gen Top001incomeshare_ipolate_lag=Top001incomeshare_ipolate[_n-1]
{txt}
{com}. qby countryn: gen Top001incomeshare_ipolate_lag2=Top001incomeshare_ipolate[_n-2]
{txt}
{com}. qby countryn: gen Top001incomeshare_ipolate_lag3=Top001incomeshare_ipolate[_n-3]
{txt}
{com}. 
. qby countryn: gen rgdppc_lag=rgdppc[_n-1]
{txt}
{com}. 
. * Table 1 
. 
. xi: reg top_incrate_nl top_incrate_nl_lag Top1incomeshare_ipolate_lag year i.country if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity

Linear regression                               Number of obs     = {res}       290
                                                {txt}F(19, 270)        =  {res}    46.34
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.7373
                                                {txt}Root MSE          =    {res} 11.181

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}             top_incrate_nl{col 29}{c |}      Coef.{col 41}   Std. Err.{col 53}      t{col 61}   P>|t|{col 69}     [95% Con{col 82}f. Interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}top_incrate_nl_lag {c |}{col 29}{res}{space 2} .8040809{col 41}{space 2} .0611056{col 52}{space 1}   13.16{col 61}{space 3}0.000{col 69}{space 4} .6837768{col 82}{space 3} .9243851
{txt}Top1incomeshare_ipolate_lag {c |}{col 29}{res}{space 2} .0358335{col 41}{space 2} .3113807{col 52}{space 1}    0.12{col 61}{space 3}0.908{col 69}{space 4}-.5772094{col 82}{space 3} .6488765
{txt}{space 23}year {c |}{col 29}{res}{space 2}-.0632512{col 41}{space 2} .0327391{col 52}{space 1}   -1.93{col 61}{space 3}0.054{col 69}{space 4}-.1277076{col 82}{space 3} .0012053
{txt}{space 16}_Icountry_2 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_3 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_4 {c |}{col 29}{res}{space 2}-.5586923{col 41}{space 2} 3.902579{col 52}{space 1}   -0.14{col 61}{space 3}0.886{col 69}{space 4}-8.242046{col 82}{space 3} 7.124662
{txt}{space 16}_Icountry_5 {c |}{col 29}{res}{space 2}-.7262678{col 41}{space 2} 2.846023{col 52}{space 1}   -0.26{col 61}{space 3}0.799{col 69}{space 4}-6.329486{col 82}{space 3}  4.87695
{txt}{space 16}_Icountry_6 {c |}{col 29}{res}{space 2}-.3554107{col 41}{space 2} 3.314157{col 52}{space 1}   -0.11{col 61}{space 3}0.915{col 69}{space 4}-6.880286{col 82}{space 3} 6.169465
{txt}{space 16}_Icountry_7 {c |}{col 29}{res}{space 2}-.8694167{col 41}{space 2} 3.769891{col 52}{space 1}   -0.23{col 61}{space 3}0.818{col 69}{space 4}-8.291537{col 82}{space 3} 6.552704
{txt}{space 16}_Icountry_8 {c |}{col 29}{res}{space 2}-2.340611{col 41}{space 2} 3.952462{col 52}{space 1}   -0.59{col 61}{space 3}0.554{col 69}{space 4}-10.12218{col 82}{space 3} 5.440954
{txt}{space 16}_Icountry_9 {c |}{col 29}{res}{space 2}-.0427385{col 41}{space 2}  3.13854{col 52}{space 1}   -0.01{col 61}{space 3}0.989{col 69}{space 4}-6.221862{col 82}{space 3} 6.136385
{txt}{space 15}_Icountry_10 {c |}{col 29}{res}{space 2} -2.11846{col 41}{space 2}  3.11271{col 52}{space 1}   -0.68{col 61}{space 3}0.497{col 69}{space 4}-8.246729{col 82}{space 3}  4.00981
{txt}{space 15}_Icountry_11 {c |}{col 29}{res}{space 2} .7594721{col 41}{space 2} 3.353484{col 52}{space 1}    0.23{col 61}{space 3}0.821{col 69}{space 4} -5.84283{col 82}{space 3} 7.361774
{txt}{space 15}_Icountry_12 {c |}{col 29}{res}{space 2} .3393601{col 41}{space 2} 3.500663{col 52}{space 1}    0.10{col 61}{space 3}0.923{col 69}{space 4}-6.552707{col 82}{space 3} 7.231427
{txt}{space 15}_Icountry_13 {c |}{col 29}{res}{space 2}-.4455092{col 41}{space 2} 4.019775{col 52}{space 1}   -0.11{col 61}{space 3}0.912{col 69}{space 4}-8.359598{col 82}{space 3} 7.468579
{txt}{space 15}_Icountry_14 {c |}{col 29}{res}{space 2} .8031322{col 41}{space 2} 3.410529{col 52}{space 1}    0.24{col 61}{space 3}0.814{col 69}{space 4} -5.91148{col 82}{space 3} 7.517745
{txt}{space 15}_Icountry_15 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 15}_Icountry_16 {c |}{col 29}{res}{space 2} -3.23792{col 41}{space 2} 2.869158{col 52}{space 1}   -1.13{col 61}{space 3}0.260{col 69}{space 4}-8.886686{col 82}{space 3} 2.410846
{txt}{space 15}_Icountry_17 {c |}{col 29}{res}{space 2} 1.756465{col 41}{space 2} 3.203802{col 52}{space 1}    0.55{col 61}{space 3}0.584{col 69}{space 4}-4.551145{col 82}{space 3} 8.064076
{txt}{space 15}_Icountry_18 {c |}{col 29}{res}{space 2}-3.282499{col 41}{space 2} 2.858507{col 52}{space 1}   -1.15{col 61}{space 3}0.252{col 69}{space 4}-8.910296{col 82}{space 3} 2.345297
{txt}{space 15}_Icountry_19 {c |}{col 29}{res}{space 2}  1.65544{col 41}{space 2} 3.976941{col 52}{space 1}    0.42{col 61}{space 3}0.678{col 69}{space 4}-6.174317{col 82}{space 3} 9.485198
{txt}{space 15}_Icountry_20 {c |}{col 29}{res}{space 2} 3.847879{col 41}{space 2} 6.288906{col 52}{space 1}    0.61{col 61}{space 3}0.541{col 69}{space 4}-8.533651{col 82}{space 3} 16.22941
{txt}{space 22}_cons {c |}{col 29}{res}{space 2}  135.463{col 41}{space 2} 68.47227{col 52}{space 1}    1.98{col 61}{space 3}0.049{col 69}{space 4} .6555781{col 82}{space 3} 270.2705
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg top_incrate_nl top_incrate_nl_lag Top1incomeshare_ipolate_lag i.country i.year if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
i.year{col 19}_Iyear_1860-2010{col 39}(naturally coded; _Iyear_1860 omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Iyear_1865 omitted because of collinearity
note: _Iyear_1870 omitted because of collinearity
note: _Iyear_1875 omitted because of collinearity
note: _Iyear_1880 omitted because of collinearity
note: _Iyear_1885 omitted because of collinearity
note: _Iyear_1890 omitted because of collinearity
note: _Iyear_1895 omitted because of collinearity
note: _Iyear_1900 omitted because of collinearity

Linear regression                               Number of obs     = {res}       290
                                                {txt}F(40, 249)        =  {res}   203.85
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8347
                                                {txt}Root MSE          =    {res} 9.2353

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}             top_incrate_nl{col 29}{c |}      Coef.{col 41}   Std. Err.{col 53}      t{col 61}   P>|t|{col 69}     [95% Con{col 82}f. Interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}top_incrate_nl_lag {c |}{col 29}{res}{space 2} .6082611{col 41}{space 2} .0756048{col 52}{space 1}    8.05{col 61}{space 3}0.000{col 69}{space 4} .4593548{col 82}{space 3} .7571675
{txt}Top1incomeshare_ipolate_lag {c |}{col 29}{res}{space 2}-.4284565{col 41}{space 2} .3899614{col 52}{space 1}   -1.10{col 61}{space 3}0.273{col 69}{space 4}  -1.1965{col 82}{space 3} .3395869
{txt}{space 16}_Icountry_2 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_3 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_4 {c |}{col 29}{res}{space 2} 2.604654{col 41}{space 2}  3.11183{col 52}{space 1}    0.84{col 61}{space 3}0.403{col 69}{space 4}-3.524209{col 82}{space 3} 8.733517
{txt}{space 16}_Icountry_5 {c |}{col 29}{res}{space 2}-.4145534{col 41}{space 2} 2.524175{col 52}{space 1}   -0.16{col 61}{space 3}0.870{col 69}{space 4}-5.386009{col 82}{space 3} 4.556902
{txt}{space 16}_Icountry_6 {c |}{col 29}{res}{space 2}-1.169395{col 41}{space 2} 2.915621{col 52}{space 1}   -0.40{col 61}{space 3}0.689{col 69}{space 4}-6.911819{col 82}{space 3} 4.573028
{txt}{space 16}_Icountry_7 {c |}{col 29}{res}{space 2} .1902692{col 41}{space 2} 2.808124{col 52}{space 1}    0.07{col 61}{space 3}0.946{col 69}{space 4}-5.340434{col 82}{space 3} 5.720973
{txt}{space 16}_Icountry_8 {c |}{col 29}{res}{space 2}  .667828{col 41}{space 2} 2.920175{col 52}{space 1}    0.23{col 61}{space 3}0.819{col 69}{space 4}-5.083564{col 82}{space 3}  6.41922
{txt}{space 16}_Icountry_9 {c |}{col 29}{res}{space 2} 1.243865{col 41}{space 2} 2.601005{col 52}{space 1}    0.48{col 61}{space 3}0.633{col 69}{space 4} -3.87891{col 82}{space 3} 6.366639
{txt}{space 15}_Icountry_10 {c |}{col 29}{res}{space 2} 1.122101{col 41}{space 2} 2.143716{col 52}{space 1}    0.52{col 61}{space 3}0.601{col 69}{space 4}-3.100027{col 82}{space 3} 5.344228
{txt}{space 15}_Icountry_11 {c |}{col 29}{res}{space 2} 5.328433{col 41}{space 2} 2.643546{col 52}{space 1}    2.02{col 61}{space 3}0.045{col 69}{space 4} .1218709{col 82}{space 3} 10.53499
{txt}{space 15}_Icountry_12 {c |}{col 29}{res}{space 2} .5476827{col 41}{space 2} 2.998797{col 52}{space 1}    0.18{col 61}{space 3}0.855{col 69}{space 4}-5.358558{col 82}{space 3} 6.453924
{txt}{space 15}_Icountry_13 {c |}{col 29}{res}{space 2}-2.252189{col 41}{space 2} 2.973305{col 52}{space 1}   -0.76{col 61}{space 3}0.449{col 69}{space 4}-8.108223{col 82}{space 3} 3.603845
{txt}{space 15}_Icountry_14 {c |}{col 29}{res}{space 2} 1.912431{col 41}{space 2} 3.332247{col 52}{space 1}    0.57{col 61}{space 3}0.567{col 69}{space 4}-4.650552{col 82}{space 3} 8.475415
{txt}{space 15}_Icountry_15 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 15}_Icountry_16 {c |}{col 29}{res}{space 2} .8415654{col 41}{space 2} 2.436409{col 52}{space 1}    0.35{col 61}{space 3}0.730{col 69}{space 4}-3.957033{col 82}{space 3} 5.640164
{txt}{space 15}_Icountry_17 {c |}{col 29}{res}{space 2} 4.369279{col 41}{space 2} 2.274126{col 52}{space 1}    1.92{col 61}{space 3}0.056{col 69}{space 4}-.1096962{col 82}{space 3} 8.848255
{txt}{space 15}_Icountry_18 {c |}{col 29}{res}{space 2}-8.063229{col 41}{space 2} 3.468391{col 52}{space 1}   -2.32{col 61}{space 3}0.021{col 69}{space 4}-14.89435{col 82}{space 3}-1.232104
{txt}{space 15}_Icountry_19 {c |}{col 29}{res}{space 2} 5.997975{col 41}{space 2} 3.621294{col 52}{space 1}    1.66{col 61}{space 3}0.099{col 69}{space 4}-1.134296{col 82}{space 3} 13.13025
{txt}{space 15}_Icountry_20 {c |}{col 29}{res}{space 2} 7.640181{col 41}{space 2} 4.839537{col 52}{space 1}    1.58{col 61}{space 3}0.116{col 69}{space 4}-1.891465{col 82}{space 3} 17.17183
{txt}{space 16}_Iyear_1865 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1870 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1875 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1880 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1885 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1890 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1895 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1900 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1905 {c |}{col 29}{res}{space 2} 7.800083{col 41}{space 2} 4.204812{col 52}{space 1}    1.86{col 61}{space 3}0.065{col 69}{space 4}-.4814488{col 82}{space 3} 16.08162
{txt}{space 16}_Iyear_1910 {c |}{col 29}{res}{space 2} 4.045326{col 41}{space 2} 3.147548{col 52}{space 1}    1.29{col 61}{space 3}0.200{col 69}{space 4}-2.153886{col 82}{space 3} 10.24454
{txt}{space 16}_Iyear_1915 {c |}{col 29}{res}{space 2} 4.644604{col 41}{space 2} 2.740376{col 52}{space 1}    1.69{col 61}{space 3}0.091{col 69}{space 4}-.7526664{col 82}{space 3} 10.04188
{txt}{space 16}_Iyear_1920 {c |}{col 29}{res}{space 2} 32.98696{col 41}{space 2} 9.545972{col 52}{space 1}    3.46{col 61}{space 3}0.001{col 69}{space 4} 14.18582{col 82}{space 3}  51.7881
{txt}{space 16}_Iyear_1925 {c |}{col 29}{res}{space 2} 11.65969{col 41}{space 2} 6.778596{col 52}{space 1}    1.72{col 61}{space 3}0.087{col 69}{space 4}-1.691003{col 82}{space 3} 25.01039
{txt}{space 16}_Iyear_1930 {c |}{col 29}{res}{space 2} 11.44804{col 41}{space 2} 3.848026{col 52}{space 1}    2.98{col 61}{space 3}0.003{col 69}{space 4} 3.869208{col 82}{space 3} 19.02687
{txt}{space 16}_Iyear_1935 {c |}{col 29}{res}{space 2}  21.5011{col 41}{space 2} 5.138948{col 52}{space 1}    4.18{col 61}{space 3}0.000{col 69}{space 4} 11.37975{col 82}{space 3} 31.62245
{txt}{space 16}_Iyear_1940 {c |}{col 29}{res}{space 2} 31.10665{col 41}{space 2} 5.521991{col 52}{space 1}    5.63{col 61}{space 3}0.000{col 69}{space 4} 20.23088{col 82}{space 3} 41.98241
{txt}{space 16}_Iyear_1945 {c |}{col 29}{res}{space 2} 32.56674{col 41}{space 2}  6.22966{col 52}{space 1}    5.23{col 61}{space 3}0.000{col 69}{space 4}  20.2972{col 82}{space 3} 44.83629
{txt}{space 16}_Iyear_1950 {c |}{col 29}{res}{space 2} 24.36422{col 41}{space 2} 5.959547{col 52}{space 1}    4.09{col 61}{space 3}0.000{col 69}{space 4} 12.62667{col 82}{space 3} 36.10176
{txt}{space 16}_Iyear_1955 {c |}{col 29}{res}{space 2} 24.12498{col 41}{space 2} 5.271207{col 52}{space 1}    4.58{col 61}{space 3}0.000{col 69}{space 4} 13.74314{col 82}{space 3} 34.50682
{txt}{space 16}_Iyear_1960 {c |}{col 29}{res}{space 2} 23.75134{col 41}{space 2} 5.041966{col 52}{space 1}    4.71{col 61}{space 3}0.000{col 69}{space 4} 13.82101{col 82}{space 3} 33.68168
{txt}{space 16}_Iyear_1965 {c |}{col 29}{res}{space 2} 22.59968{col 41}{space 2} 4.945392{col 52}{space 1}    4.57{col 61}{space 3}0.000{col 69}{space 4} 12.85955{col 82}{space 3} 32.33981
{txt}{space 16}_Iyear_1970 {c |}{col 29}{res}{space 2} 25.87646{col 41}{space 2} 4.918622{col 52}{space 1}    5.26{col 61}{space 3}0.000{col 69}{space 4} 16.18906{col 82}{space 3} 35.56387
{txt}{space 16}_Iyear_1975 {c |}{col 29}{res}{space 2}  21.8419{col 41}{space 2} 5.175314{col 52}{space 1}    4.22{col 61}{space 3}0.000{col 69}{space 4} 11.64892{col 82}{space 3} 32.03487
{txt}{space 16}_Iyear_1980 {c |}{col 29}{res}{space 2} 21.24472{col 41}{space 2} 5.022258{col 52}{space 1}    4.23{col 61}{space 3}0.000{col 69}{space 4}  11.3532{col 82}{space 3} 31.13624
{txt}{space 16}_Iyear_1985 {c |}{col 29}{res}{space 2} 19.15805{col 41}{space 2} 4.995925{col 52}{space 1}    3.83{col 61}{space 3}0.000{col 69}{space 4} 9.318395{col 82}{space 3} 28.99771
{txt}{space 16}_Iyear_1990 {c |}{col 29}{res}{space 2}   8.3588{col 41}{space 2} 5.150952{col 52}{space 1}    1.62{col 61}{space 3}0.106{col 69}{space 4}-1.786191{col 82}{space 3} 18.50379
{txt}{space 16}_Iyear_1995 {c |}{col 29}{res}{space 2} 16.11303{col 41}{space 2} 4.081139{col 52}{space 1}    3.95{col 61}{space 3}0.000{col 69}{space 4} 8.075078{col 82}{space 3} 24.15098
{txt}{space 16}_Iyear_2000 {c |}{col 29}{res}{space 2} 14.35544{col 41}{space 2} 4.046102{col 52}{space 1}    3.55{col 61}{space 3}0.000{col 69}{space 4} 6.386489{col 82}{space 3} 22.32438
{txt}{space 16}_Iyear_2005 {c |}{col 29}{res}{space 2}  13.7004{col 41}{space 2} 3.833847{col 52}{space 1}    3.57{col 61}{space 3}0.000{col 69}{space 4} 6.149501{col 82}{space 3} 21.25131
{txt}{space 16}_Iyear_2010 {c |}{col 29}{res}{space 2} 14.31542{col 41}{space 2} 3.744383{col 52}{space 1}    3.82{col 61}{space 3}0.000{col 69}{space 4}  6.94072{col 82}{space 3} 21.69012
{txt}{space 22}_cons {c |}{col 29}{res}{space 2}  5.96197{col 41}{space 2}  5.99544{col 52}{space 1}    0.99{col 61}{space 3}0.321{col 69}{space 4}-5.846271{col 82}{space 3} 17.77021
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg Top1incomeshare_ipolate Top1incomeshare_ipolate_lag top_incrate_nl_lag year i.country if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity

Linear regression                               Number of obs     = {res}       284
                                                {txt}F(19, 264)        =  {res}    81.43
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8205
                                                {txt}Root MSE          =    {res} 1.7865

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}    Top1incomeshare_ipolate{col 29}{c |}      Coef.{col 41}   Std. Err.{col 53}      t{col 61}   P>|t|{col 69}     [95% Con{col 82}f. Interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Top1incomeshare_ipolate_lag {c |}{col 29}{res}{space 2}  .541069{col 41}{space 2} .0814572{col 52}{space 1}    6.64{col 61}{space 3}0.000{col 69}{space 4} .3806805{col 82}{space 3} .7014574
{txt}{space 9}top_incrate_nl_lag {c |}{col 29}{res}{space 2} -.052175{col 41}{space 2} .0084314{col 52}{space 1}   -6.19{col 61}{space 3}0.000{col 69}{space 4}-.0687763{col 82}{space 3}-.0355738
{txt}{space 23}year {c |}{col 29}{res}{space 2}-.0167367{col 41}{space 2}  .008304{col 52}{space 1}   -2.02{col 61}{space 3}0.045{col 69}{space 4}-.0330872{col 82}{space 3}-.0003863
{txt}{space 16}_Icountry_2 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_3 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_4 {c |}{col 29}{res}{space 2} 1.725475{col 41}{space 2} .7323446{col 52}{space 1}    2.36{col 61}{space 3}0.019{col 69}{space 4} .2834959{col 82}{space 3} 3.167455
{txt}{space 16}_Icountry_5 {c |}{col 29}{res}{space 2}  -.13341{col 41}{space 2} .6803255{col 52}{space 1}   -0.20{col 61}{space 3}0.845{col 69}{space 4}-1.472964{col 82}{space 3} 1.206144
{txt}{space 16}_Icountry_6 {c |}{col 29}{res}{space 2}-.5072674{col 41}{space 2} .6779507{col 52}{space 1}   -0.75{col 61}{space 3}0.455{col 69}{space 4}-1.842146{col 82}{space 3}  .827611
{txt}{space 16}_Icountry_7 {c |}{col 29}{res}{space 2} .4202589{col 41}{space 2} .6613806{col 52}{space 1}    0.64{col 61}{space 3}0.526{col 69}{space 4}-.8819932{col 82}{space 3} 1.722511
{txt}{space 16}_Icountry_8 {c |}{col 29}{res}{space 2} .7704741{col 41}{space 2} .6943487{col 52}{space 1}    1.11{col 61}{space 3}0.268{col 69}{space 4}-.5966919{col 82}{space 3}  2.13764
{txt}{space 16}_Icountry_9 {c |}{col 29}{res}{space 2} .7198046{col 41}{space 2} .6392722{col 52}{space 1}    1.13{col 61}{space 3}0.261{col 69}{space 4}-.5389164{col 82}{space 3} 1.978526
{txt}{space 15}_Icountry_10 {c |}{col 29}{res}{space 2} .7213663{col 41}{space 2} .5682703{col 52}{space 1}    1.27{col 61}{space 3}0.205{col 69}{space 4}-.3975526{col 82}{space 3} 1.840285
{txt}{space 15}_Icountry_11 {c |}{col 29}{res}{space 2} 1.231338{col 41}{space 2} .6999326{col 52}{space 1}    1.76{col 61}{space 3}0.080{col 69}{space 4}-.1468222{col 82}{space 3} 2.609499
{txt}{space 15}_Icountry_12 {c |}{col 29}{res}{space 2} .1966332{col 41}{space 2} .6481309{col 52}{space 1}    0.30{col 61}{space 3}0.762{col 69}{space 4} -1.07953{col 82}{space 3} 1.472797
{txt}{space 15}_Icountry_13 {c |}{col 29}{res}{space 2}-.5977993{col 41}{space 2} .6321559{col 52}{space 1}   -0.95{col 61}{space 3}0.345{col 69}{space 4}-1.842508{col 82}{space 3} .6469097
{txt}{space 15}_Icountry_14 {c |}{col 29}{res}{space 2} .1918728{col 41}{space 2} .7632715{col 52}{space 1}    0.25{col 61}{space 3}0.802{col 69}{space 4}-1.311002{col 82}{space 3} 1.694747
{txt}{space 15}_Icountry_15 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 15}_Icountry_16 {c |}{col 29}{res}{space 2} .4919978{col 41}{space 2} .6126578{col 52}{space 1}    0.80{col 61}{space 3}0.423{col 69}{space 4}-.7143196{col 82}{space 3} 1.698315
{txt}{space 15}_Icountry_17 {c |}{col 29}{res}{space 2}-.0203297{col 41}{space 2} .7588255{col 52}{space 1}   -0.03{col 61}{space 3}0.979{col 69}{space 4} -1.51445{col 82}{space 3}  1.47379
{txt}{space 15}_Icountry_18 {c |}{col 29}{res}{space 2}-.3287178{col 41}{space 2}  .557403{col 52}{space 1}   -0.59{col 61}{space 3}0.556{col 69}{space 4}-1.426239{col 82}{space 3} .7688035
{txt}{space 15}_Icountry_19 {c |}{col 29}{res}{space 2} 1.954169{col 41}{space 2} .7447252{col 52}{space 1}    2.62{col 61}{space 3}0.009{col 69}{space 4} .4878126{col 82}{space 3} 3.420526
{txt}{space 15}_Icountry_20 {c |}{col 29}{res}{space 2} 2.508206{col 41}{space 2}   .88118{col 52}{space 1}    2.85{col 61}{space 3}0.005{col 69}{space 4} .7731711{col 82}{space 3} 4.243241
{txt}{space 22}_cons {c |}{col 29}{res}{space 2} 39.69908{col 41}{space 2} 17.06809{col 52}{space 1}    2.33{col 61}{space 3}0.021{col 69}{space 4} 6.092171{col 82}{space 3} 73.30598
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg Top1incomeshare_ipolate Top1incomeshare_ipolate_lag top_incrate_nl_lag i.country i.year if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
i.year{col 19}_Iyear_1860-2010{col 39}(naturally coded; _Iyear_1860 omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Iyear_1865 omitted because of collinearity
note: _Iyear_1870 omitted because of collinearity
note: _Iyear_1875 omitted because of collinearity
note: _Iyear_1880 omitted because of collinearity
note: _Iyear_1885 omitted because of collinearity
note: _Iyear_1890 omitted because of collinearity
note: _Iyear_1895 omitted because of collinearity
note: _Iyear_1905 omitted because of collinearity

Linear regression                               Number of obs     = {res}       284
                                                {txt}F(40, 243)        =  {res}   478.43
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8768
                                                {txt}Root MSE          =    {res} 1.5428

{txt}{hline 28}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 29}{c |}{col 41}    Robust
{col 1}    Top1incomeshare_ipolate{col 29}{c |}      Coef.{col 41}   Std. Err.{col 53}      t{col 61}   P>|t|{col 69}     [95% Con{col 82}f. Interval]
{hline 28}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Top1incomeshare_ipolate_lag {c |}{col 29}{res}{space 2} .5771881{col 41}{space 2} .0791754{col 52}{space 1}    7.29{col 61}{space 3}0.000{col 69}{space 4} .4212304{col 82}{space 3} .7331459
{txt}{space 9}top_incrate_nl_lag {c |}{col 29}{res}{space 2}-.0213489{col 41}{space 2} .0091502{col 52}{space 1}   -2.33{col 61}{space 3}0.020{col 69}{space 4}-.0393727{col 82}{space 3}-.0033251
{txt}{space 16}_Icountry_2 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_3 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Icountry_4 {c |}{col 29}{res}{space 2} 1.424125{col 41}{space 2} .6225803{col 52}{space 1}    2.29{col 61}{space 3}0.023{col 69}{space 4} .1977821{col 82}{space 3} 2.650467
{txt}{space 16}_Icountry_5 {c |}{col 29}{res}{space 2}-.0526912{col 41}{space 2} .5511764{col 52}{space 1}   -0.10{col 61}{space 3}0.924{col 69}{space 4}-1.138384{col 82}{space 3} 1.033002
{txt}{space 16}_Icountry_6 {c |}{col 29}{res}{space 2}-.2999467{col 41}{space 2} .5731656{col 52}{space 1}   -0.52{col 61}{space 3}0.601{col 69}{space 4}-1.428954{col 82}{space 3} .8290603
{txt}{space 16}_Icountry_7 {c |}{col 29}{res}{space 2} .4036779{col 41}{space 2} .5951145{col 52}{space 1}    0.68{col 61}{space 3}0.498{col 69}{space 4}-.7685633{col 82}{space 3} 1.575919
{txt}{space 16}_Icountry_8 {c |}{col 29}{res}{space 2}  .767016{col 41}{space 2} .7143053{col 52}{space 1}    1.07{col 61}{space 3}0.284{col 69}{space 4}-.6400042{col 82}{space 3} 2.174036
{txt}{space 16}_Icountry_9 {c |}{col 29}{res}{space 2} .6576307{col 41}{space 2} .5640195{col 52}{space 1}    1.17{col 61}{space 3}0.245{col 69}{space 4}-.4533604{col 82}{space 3} 1.768622
{txt}{space 15}_Icountry_10 {c |}{col 29}{res}{space 2} .3813307{col 41}{space 2} .5234578{col 52}{space 1}    0.73{col 61}{space 3}0.467{col 69}{space 4}-.6497631{col 82}{space 3} 1.412425
{txt}{space 15}_Icountry_11 {c |}{col 29}{res}{space 2} .7881217{col 41}{space 2} .6566763{col 52}{space 1}    1.20{col 61}{space 3}0.231{col 69}{space 4}-.5053825{col 82}{space 3} 2.081626
{txt}{space 15}_Icountry_12 {c |}{col 29}{res}{space 2} .3353257{col 41}{space 2} .6076137{col 52}{space 1}    0.55{col 61}{space 3}0.582{col 69}{space 4}-.8615361{col 82}{space 3} 1.532188
{txt}{space 15}_Icountry_13 {c |}{col 29}{res}{space 2}-.3162389{col 41}{space 2} .5624621{col 52}{space 1}   -0.56{col 61}{space 3}0.574{col 69}{space 4}-1.424162{col 82}{space 3} .7916846
{txt}{space 15}_Icountry_14 {c |}{col 29}{res}{space 2} .0294454{col 41}{space 2} .7060088{col 52}{space 1}    0.04{col 61}{space 3}0.967{col 69}{space 4}-1.361233{col 82}{space 3} 1.420123
{txt}{space 15}_Icountry_15 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 15}_Icountry_16 {c |}{col 29}{res}{space 2}-.0036059{col 41}{space 2} .5500601{col 52}{space 1}   -0.01{col 61}{space 3}0.995{col 69}{space 4}  -1.0871{col 82}{space 3} 1.079888
{txt}{space 15}_Icountry_17 {c |}{col 29}{res}{space 2}-.3180362{col 41}{space 2} .6218497{col 52}{space 1}   -0.51{col 61}{space 3}0.610{col 69}{space 4} -1.54294{col 82}{space 3} .9068674
{txt}{space 15}_Icountry_18 {c |}{col 29}{res}{space 2} .4912547{col 41}{space 2} .5072589{col 52}{space 1}    0.97{col 61}{space 3}0.334{col 69}{space 4}-.5079309{col 82}{space 3}  1.49044
{txt}{space 15}_Icountry_19 {c |}{col 29}{res}{space 2} 1.470375{col 41}{space 2} .6546942{col 52}{space 1}    2.25{col 61}{space 3}0.026{col 69}{space 4} .1807751{col 82}{space 3} 2.759975
{txt}{space 15}_Icountry_20 {c |}{col 29}{res}{space 2} 2.122037{col 41}{space 2} .7451919{col 52}{space 1}    2.85{col 61}{space 3}0.005{col 69}{space 4} .6541774{col 82}{space 3} 3.589897
{txt}{space 16}_Iyear_1865 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1870 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1875 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1880 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1885 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1890 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1895 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1900 {c |}{col 29}{res}{space 2} .8028622{col 41}{space 2}   .51864{col 52}{space 1}    1.55{col 61}{space 3}0.123{col 69}{space 4}-.2187415{col 82}{space 3} 1.824466
{txt}{space 16}_Iyear_1905 {c |}{col 29}{res}{space 2}        0{col 41}{txt}  (omitted)
{space 16}_Iyear_1910 {c |}{col 29}{res}{space 2} .0909994{col 41}{space 2} .8130044{col 52}{space 1}    0.11{col 61}{space 3}0.911{col 69}{space 4}-1.510436{col 82}{space 3} 1.692435
{txt}{space 16}_Iyear_1915 {c |}{col 29}{res}{space 2} 2.467719{col 41}{space 2}  1.50831{col 52}{space 1}    1.64{col 61}{space 3}0.103{col 69}{space 4}-.5033117{col 82}{space 3} 5.438749
{txt}{space 16}_Iyear_1920 {c |}{col 29}{res}{space 2}-3.256736{col 41}{space 2} 1.077195{col 52}{space 1}   -3.02{col 61}{space 3}0.003{col 69}{space 4}-5.378566{col 82}{space 3}-1.134906
{txt}{space 16}_Iyear_1925 {c |}{col 29}{res}{space 2}-1.315505{col 41}{space 2} .9098812{col 52}{space 1}   -1.45{col 61}{space 3}0.150{col 69}{space 4}-3.107766{col 82}{space 3} .4767555
{txt}{space 16}_Iyear_1930 {c |}{col 29}{res}{space 2}-1.230948{col 41}{space 2} .6994065{col 52}{space 1}   -1.76{col 61}{space 3}0.080{col 69}{space 4}-2.608621{col 82}{space 3} .1467246
{txt}{space 16}_Iyear_1935 {c |}{col 29}{res}{space 2} -1.29068{col 41}{space 2} .7623347{col 52}{space 1}   -1.69{col 61}{space 3}0.092{col 69}{space 4}-2.792307{col 82}{space 3} .2109474
{txt}{space 16}_Iyear_1940 {c |}{col 29}{res}{space 2}-1.605878{col 41}{space 2} .8304326{col 52}{space 1}   -1.93{col 61}{space 3}0.054{col 69}{space 4}-3.241642{col 82}{space 3} .0298872
{txt}{space 16}_Iyear_1945 {c |}{col 29}{res}{space 2}-4.123067{col 41}{space 2} 1.019194{col 52}{space 1}   -4.05{col 61}{space 3}0.000{col 69}{space 4}-6.130649{col 82}{space 3}-2.115485
{txt}{space 16}_Iyear_1950 {c |}{col 29}{res}{space 2}-2.134246{col 41}{space 2} .8642294{col 52}{space 1}   -2.47{col 61}{space 3}0.014{col 69}{space 4}-3.836583{col 82}{space 3}-.4319094
{txt}{space 16}_Iyear_1955 {c |}{col 29}{res}{space 2}-3.288913{col 41}{space 2} .9336427{col 52}{space 1}   -3.52{col 61}{space 3}0.001{col 69}{space 4}-5.127978{col 82}{space 3}-1.449847
{txt}{space 16}_Iyear_1960 {c |}{col 29}{res}{space 2}-2.805346{col 41}{space 2} .9014492{col 52}{space 1}   -3.11{col 61}{space 3}0.002{col 69}{space 4}-4.580997{col 82}{space 3}-1.029694
{txt}{space 16}_Iyear_1965 {c |}{col 29}{res}{space 2}-3.091626{col 41}{space 2}  .903296{col 52}{space 1}   -3.42{col 61}{space 3}0.001{col 69}{space 4}-4.870916{col 82}{space 3}-1.312337
{txt}{space 16}_Iyear_1970 {c |}{col 29}{res}{space 2}-3.224658{col 41}{space 2}  .924591{col 52}{space 1}   -3.49{col 61}{space 3}0.001{col 69}{space 4}-5.045894{col 82}{space 3}-1.403422
{txt}{space 16}_Iyear_1975 {c |}{col 29}{res}{space 2}-4.110158{col 41}{space 2} .9399448{col 52}{space 1}   -4.37{col 61}{space 3}0.000{col 69}{space 4}-5.961638{col 82}{space 3}-2.258679
{txt}{space 16}_Iyear_1980 {c |}{col 29}{res}{space 2}-3.922345{col 41}{space 2} .9819416{col 52}{space 1}   -3.99{col 61}{space 3}0.000{col 69}{space 4}-5.856549{col 82}{space 3}-1.988142
{txt}{space 16}_Iyear_1985 {c |}{col 29}{res}{space 2}-3.675259{col 41}{space 2} .9823473{col 52}{space 1}   -3.74{col 61}{space 3}0.000{col 69}{space 4}-5.610262{col 82}{space 3}-1.740257
{txt}{space 16}_Iyear_1990 {c |}{col 29}{res}{space 2}-2.708594{col 41}{space 2} 1.009465{col 52}{space 1}   -2.68{col 61}{space 3}0.008{col 69}{space 4}-4.697011{col 82}{space 3}-.7201767
{txt}{space 16}_Iyear_1995 {c |}{col 29}{res}{space 2}-3.128214{col 41}{space 2} .9138529{col 52}{space 1}   -3.42{col 61}{space 3}0.001{col 69}{space 4}-4.928298{col 82}{space 3} -1.32813
{txt}{space 16}_Iyear_2000 {c |}{col 29}{res}{space 2}-1.820828{col 41}{space 2} .9437613{col 52}{space 1}   -1.93{col 61}{space 3}0.055{col 69}{space 4}-3.679825{col 82}{space 3} .0381685
{txt}{space 16}_Iyear_2005 {c |}{col 29}{res}{space 2}-2.021952{col 41}{space 2} 1.023336{col 52}{space 1}   -1.98{col 61}{space 3}0.049{col 69}{space 4}-4.037692{col 82}{space 3}-.0062112
{txt}{space 16}_Iyear_2010 {c |}{col 29}{res}{space 2}-3.559432{col 41}{space 2} 1.059905{col 52}{space 1}   -3.36{col 61}{space 3}0.001{col 69}{space 4}-5.647206{col 82}{space 3}-1.471659
{txt}{space 22}_cons {c |}{col 29}{res}{space 2} 7.399792{col 41}{space 2} 1.369572{col 52}{space 1}    5.40{col 61}{space 3}0.000{col 69}{space 4} 4.702044{col 82}{space 3} 10.09754
{txt}{hline 28}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * Table 2  
. 
. xi: reg top_incrate_nl top_incrate_nl_lag Top001incomeshare_ipolate_lag year i.country if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_6 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_13 omitted because of collinearity
note: _Icountry_14 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_18 omitted because of collinearity

Linear regression                               Number of obs     = {res}       200
                                                {txt}F(14, 185)        =  {res}    29.28
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.7222
                                                {txt}Root MSE          =    {res} 12.197

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}               top_incrate_nl{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}top_incrate_nl_lag {c |}{col 31}{res}{space 2} .7858477{col 43}{space 2} .0770638{col 54}{space 1}   10.20{col 63}{space 3}0.000{col 71}{space 4} .6338109{col 84}{space 3} .9378845
{txt}Top001incomeshare_ipolate_lag {c |}{col 31}{res}{space 2} 1.150582{col 43}{space 2} 2.044977{col 54}{space 1}    0.56{col 63}{space 3}0.574{col 71}{space 4}-2.883891{col 84}{space 3} 5.185055
{txt}{space 25}year {c |}{col 31}{res}{space 2}-.0273861{col 43}{space 2} .0404623{col 54}{space 1}   -0.68{col 63}{space 3}0.499{col 71}{space 4}-.1072129{col 84}{space 3} .0524408
{txt}{space 18}_Icountry_2 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_3 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_4 {c |}{col 31}{res}{space 2} -.991179{col 43}{space 2} 4.186997{col 54}{space 1}   -0.24{col 63}{space 3}0.813{col 71}{space 4}-9.251579{col 84}{space 3} 7.269221
{txt}{space 18}_Icountry_5 {c |}{col 31}{res}{space 2}-.9037145{col 43}{space 2} 3.150137{col 54}{space 1}   -0.29{col 63}{space 3}0.775{col 71}{space 4}-7.118524{col 84}{space 3} 5.311095
{txt}{space 18}_Icountry_6 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_7 {c |}{col 31}{res}{space 2}-1.732898{col 43}{space 2} 4.060047{col 54}{space 1}   -0.43{col 63}{space 3}0.670{col 71}{space 4}-9.742843{col 84}{space 3} 6.277047
{txt}{space 18}_Icountry_8 {c |}{col 31}{res}{space 2}-3.796241{col 43}{space 2} 4.371899{col 54}{space 1}   -0.87{col 63}{space 3}0.386{col 71}{space 4}-12.42143{col 84}{space 3} 4.828948
{txt}{space 18}_Icountry_9 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_10 {c |}{col 31}{res}{space 2}-3.260688{col 43}{space 2} 3.482184{col 54}{space 1}   -0.94{col 63}{space 3}0.350{col 71}{space 4}-10.13058{col 84}{space 3} 3.609209
{txt}{space 17}_Icountry_11 {c |}{col 31}{res}{space 2}-.1034122{col 43}{space 2} 4.001921{col 54}{space 1}   -0.03{col 63}{space 3}0.979{col 71}{space 4}-7.998681{col 84}{space 3} 7.791857
{txt}{space 17}_Icountry_12 {c |}{col 31}{res}{space 2} 3.758783{col 43}{space 2} 4.974329{col 54}{space 1}    0.76{col 63}{space 3}0.451{col 71}{space 4}-6.054921{col 84}{space 3} 13.57249
{txt}{space 17}_Icountry_13 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_14 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_15 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_16 {c |}{col 31}{res}{space 2}-.6530601{col 43}{space 2}    3.786{col 54}{space 1}   -0.17{col 63}{space 3}0.863{col 71}{space 4}-8.122345{col 84}{space 3} 6.816225
{txt}{space 17}_Icountry_17 {c |}{col 31}{res}{space 2} 1.283772{col 43}{space 2} 3.643741{col 54}{space 1}    0.35{col 63}{space 3}0.725{col 71}{space 4}-5.904855{col 84}{space 3} 8.472398
{txt}{space 17}_Icountry_18 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_19 {c |}{col 31}{res}{space 2} 4.369058{col 43}{space 2} 5.638957{col 54}{space 1}    0.77{col 63}{space 3}0.439{col 71}{space 4}-6.755871{col 84}{space 3} 15.49399
{txt}{space 17}_Icountry_20 {c |}{col 31}{res}{space 2} 2.868835{col 43}{space 2} 6.190126{col 54}{space 1}    0.46{col 63}{space 3}0.644{col 71}{space 4}-9.343479{col 84}{space 3} 15.08115
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} 65.81069{col 43}{space 2} 80.20559{col 54}{space 1}    0.82{col 63}{space 3}0.413{col 71}{space 4}-92.42451{col 84}{space 3} 224.0459
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg top_incrate_nl top_incrate_nl_lag Top001incomeshare_ipolate_lag i.country i.year if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
i.year{col 19}_Iyear_1860-2010{col 39}(naturally coded; _Iyear_1860 omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_6 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_13 omitted because of collinearity
note: _Icountry_14 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_18 omitted because of collinearity
note: _Iyear_1865 omitted because of collinearity
note: _Iyear_1870 omitted because of collinearity
note: _Iyear_1875 omitted because of collinearity
note: _Iyear_1880 omitted because of collinearity
note: _Iyear_1885 omitted because of collinearity
note: _Iyear_1890 omitted because of collinearity
note: _Iyear_1895 omitted because of collinearity
note: _Iyear_1905 omitted because of collinearity

Linear regression                               Number of obs     = {res}       200
                                                {txt}F(35, 164)        =  {res}   271.22
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8556
                                                {txt}Root MSE          =    {res} 9.3389

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}               top_incrate_nl{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}top_incrate_nl_lag {c |}{col 31}{res}{space 2} .6301827{col 43}{space 2} .0772662{col 54}{space 1}    8.16{col 63}{space 3}0.000{col 71}{space 4} .4776179{col 84}{space 3} .7827474
{txt}Top001incomeshare_ipolate_lag {c |}{col 31}{res}{space 2} -.670235{col 43}{space 2} 2.358608{col 54}{space 1}   -0.28{col 63}{space 3}0.777{col 71}{space 4}-5.327388{col 84}{space 3} 3.986918
{txt}{space 18}_Icountry_2 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_3 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_4 {c |}{col 31}{res}{space 2} 1.903185{col 43}{space 2}  3.18513{col 54}{space 1}    0.60{col 63}{space 3}0.551{col 71}{space 4}-4.385964{col 84}{space 3} 8.192333
{txt}{space 18}_Icountry_5 {c |}{col 31}{res}{space 2}-.6668133{col 43}{space 2} 2.861453{col 54}{space 1}   -0.23{col 63}{space 3}0.816{col 71}{space 4}-6.316851{col 84}{space 3} 4.983224
{txt}{space 18}_Icountry_6 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_7 {c |}{col 31}{res}{space 2}-.3132323{col 43}{space 2} 2.820928{col 54}{space 1}   -0.11{col 63}{space 3}0.912{col 71}{space 4}-5.883252{col 84}{space 3} 5.256788
{txt}{space 18}_Icountry_8 {c |}{col 31}{res}{space 2}-.0184561{col 43}{space 2} 3.260012{col 54}{space 1}   -0.01{col 63}{space 3}0.995{col 71}{space 4}-6.455462{col 84}{space 3} 6.418549
{txt}{space 18}_Icountry_9 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_10 {c |}{col 31}{res}{space 2} .4218158{col 43}{space 2} 2.201581{col 54}{space 1}    0.19{col 63}{space 3}0.848{col 71}{space 4}-3.925282{col 84}{space 3} 4.768914
{txt}{space 17}_Icountry_11 {c |}{col 31}{res}{space 2} 4.754578{col 43}{space 2} 3.126607{col 54}{space 1}    1.52{col 63}{space 3}0.130{col 71}{space 4}-1.419015{col 84}{space 3} 10.92817
{txt}{space 17}_Icountry_12 {c |}{col 31}{res}{space 2} .5576717{col 43}{space 2}  4.29996{col 54}{space 1}    0.13{col 63}{space 3}0.897{col 71}{space 4}-7.932748{col 84}{space 3} 9.048091
{txt}{space 17}_Icountry_13 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_14 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_15 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_16 {c |}{col 31}{res}{space 2}-2.944324{col 43}{space 2} 3.152391{col 54}{space 1}   -0.93{col 63}{space 3}0.352{col 71}{space 4} -9.16883{col 84}{space 3} 3.280182
{txt}{space 17}_Icountry_17 {c |}{col 31}{res}{space 2} 4.139987{col 43}{space 2} 2.588942{col 54}{space 1}    1.60{col 63}{space 3}0.112{col 71}{space 4}-.9719676{col 84}{space 3} 9.251942
{txt}{space 17}_Icountry_18 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_19 {c |}{col 31}{res}{space 2} 8.219848{col 43}{space 2} 4.840025{col 54}{space 1}    1.70{col 63}{space 3}0.091{col 71}{space 4}-1.336949{col 84}{space 3} 17.77665
{txt}{space 17}_Icountry_20 {c |}{col 31}{res}{space 2} 6.354696{col 43}{space 2} 5.156096{col 54}{space 1}    1.23{col 63}{space 3}0.220{col 71}{space 4}-3.826194{col 84}{space 3} 16.53559
{txt}{space 18}_Iyear_1865 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1870 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1875 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1880 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1885 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1890 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1895 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1900 {c |}{col 31}{res}{space 2}-6.912068{col 43}{space 2} 4.198859{col 54}{space 1}   -1.65{col 63}{space 3}0.102{col 71}{space 4}-15.20286{col 84}{space 3} 1.378724
{txt}{space 18}_Iyear_1905 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1910 {c |}{col 31}{res}{space 2}-5.456535{col 43}{space 2} 4.200227{col 54}{space 1}   -1.30{col 63}{space 3}0.196{col 71}{space 4}-13.75003{col 84}{space 3} 2.836959
{txt}{space 18}_Iyear_1915 {c |}{col 31}{res}{space 2}-3.565908{col 43}{space 2} 4.310818{col 54}{space 1}   -0.83{col 63}{space 3}0.409{col 71}{space 4}-12.07777{col 84}{space 3} 4.945951
{txt}{space 18}_Iyear_1920 {c |}{col 31}{res}{space 2} 32.18807{col 43}{space 2} 9.092856{col 54}{space 1}    3.54{col 63}{space 3}0.001{col 71}{space 4} 14.23391{col 84}{space 3} 50.14222
{txt}{space 18}_Iyear_1925 {c |}{col 31}{res}{space 2}-1.589006{col 43}{space 2} 6.821538{col 54}{space 1}   -0.23{col 63}{space 3}0.816{col 71}{space 4}-15.05837{col 84}{space 3} 11.88036
{txt}{space 18}_Iyear_1930 {c |}{col 31}{res}{space 2} 2.240023{col 43}{space 2} 5.434723{col 54}{space 1}    0.41{col 63}{space 3}0.681{col 71}{space 4}-8.491025{col 84}{space 3} 12.97107
{txt}{space 18}_Iyear_1935 {c |}{col 31}{res}{space 2} 12.57158{col 43}{space 2} 6.923405{col 54}{space 1}    1.82{col 63}{space 3}0.071{col 71}{space 4}-1.098922{col 84}{space 3} 26.24208
{txt}{space 18}_Iyear_1940 {c |}{col 31}{res}{space 2} 20.51102{col 43}{space 2} 6.515049{col 54}{space 1}    3.15{col 63}{space 3}0.002{col 71}{space 4}  7.64683{col 84}{space 3} 33.37521
{txt}{space 18}_Iyear_1945 {c |}{col 31}{res}{space 2} 27.07351{col 43}{space 2} 7.128853{col 54}{space 1}    3.80{col 63}{space 3}0.000{col 71}{space 4} 12.99734{col 84}{space 3} 41.14968
{txt}{space 18}_Iyear_1950 {c |}{col 31}{res}{space 2} 15.10681{col 43}{space 2} 6.586364{col 54}{space 1}    2.29{col 63}{space 3}0.023{col 71}{space 4} 2.101809{col 84}{space 3} 28.11182
{txt}{space 18}_Iyear_1955 {c |}{col 31}{res}{space 2} 15.54485{col 43}{space 2} 6.847826{col 54}{space 1}    2.27{col 63}{space 3}0.025{col 71}{space 4} 2.023579{col 84}{space 3} 29.06612
{txt}{space 18}_Iyear_1960 {c |}{col 31}{res}{space 2} 17.10559{col 43}{space 2} 6.487821{col 54}{space 1}    2.64{col 63}{space 3}0.009{col 71}{space 4} 4.295168{col 84}{space 3} 29.91602
{txt}{space 18}_Iyear_1965 {c |}{col 31}{res}{space 2}   15.725{col 43}{space 2} 6.556107{col 54}{space 1}    2.40{col 63}{space 3}0.018{col 71}{space 4} 2.779738{col 84}{space 3} 28.67026
{txt}{space 18}_Iyear_1970 {c |}{col 31}{res}{space 2}  18.5972{col 43}{space 2} 6.651645{col 54}{space 1}    2.80{col 63}{space 3}0.006{col 71}{space 4} 5.463297{col 84}{space 3}  31.7311
{txt}{space 18}_Iyear_1975 {c |}{col 31}{res}{space 2}  14.2988{col 43}{space 2} 6.721441{col 54}{space 1}    2.13{col 63}{space 3}0.035{col 71}{space 4}  1.02708{col 84}{space 3} 27.57052
{txt}{space 18}_Iyear_1980 {c |}{col 31}{res}{space 2} 15.06837{col 43}{space 2} 6.931173{col 54}{space 1}    2.17{col 63}{space 3}0.031{col 71}{space 4} 1.382527{col 84}{space 3} 28.75421
{txt}{space 18}_Iyear_1985 {c |}{col 31}{res}{space 2} 12.41043{col 43}{space 2}  6.97978{col 54}{space 1}    1.78{col 63}{space 3}0.077{col 71}{space 4}-1.371386{col 84}{space 3} 26.19225
{txt}{space 18}_Iyear_1990 {c |}{col 31}{res}{space 2} 3.202314{col 43}{space 2} 7.081203{col 54}{space 1}    0.45{col 63}{space 3}0.652{col 71}{space 4}-10.77977{col 84}{space 3} 17.18439
{txt}{space 18}_Iyear_1995 {c |}{col 31}{res}{space 2}  11.2853{col 43}{space 2} 5.938459{col 54}{space 1}    1.90{col 63}{space 3}0.059{col 71}{space 4}-.4403927{col 84}{space 3} 23.01099
{txt}{space 18}_Iyear_2000 {c |}{col 31}{res}{space 2}  6.72561{col 43}{space 2} 6.070565{col 54}{space 1}    1.11{col 63}{space 3}0.270{col 71}{space 4} -5.26093{col 84}{space 3} 18.71215
{txt}{space 18}_Iyear_2005 {c |}{col 31}{res}{space 2} 6.819823{col 43}{space 2} 5.799809{col 54}{space 1}    1.18{col 63}{space 3}0.241{col 71}{space 4}-4.632101{col 84}{space 3} 18.27175
{txt}{space 18}_Iyear_2010 {c |}{col 31}{res}{space 2} 6.557415{col 43}{space 2} 5.611696{col 54}{space 1}    1.17{col 63}{space 3}0.244{col 71}{space 4}-4.523073{col 84}{space 3}  17.6379
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} 8.787414{col 43}{space 2} 7.274221{col 54}{space 1}    1.21{col 63}{space 3}0.229{col 71}{space 4}-5.575787{col 84}{space 3} 23.15061
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg Top001incomeshare_ipolate Top001incomeshare_ipolate_lag top_incrate_nl_lag year i.country if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_6 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_13 omitted because of collinearity
note: _Icountry_14 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_18 omitted because of collinearity

Linear regression                               Number of obs     = {res}       194
                                                {txt}F(14, 179)        =  {res}    48.91
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8089
                                                {txt}Root MSE          =    {res} .43974

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}    Top001incomeshare_ipolate{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Top001incomeshare_ipolate_lag {c |}{col 31}{res}{space 2} .4896319{col 43}{space 2} .1193396{col 54}{space 1}    4.10{col 63}{space 3}0.000{col 71}{space 4} .2541384{col 84}{space 3} .7251255
{txt}{space 11}top_incrate_nl_lag {c |}{col 31}{res}{space 2}-.0144979{col 43}{space 2} .0029936{col 54}{space 1}   -4.84{col 63}{space 3}0.000{col 71}{space 4}-.0204053{col 84}{space 3}-.0085906
{txt}{space 25}year {c |}{col 31}{res}{space 2}-.0007527{col 43}{space 2} .0019559{col 54}{space 1}   -0.38{col 63}{space 3}0.701{col 71}{space 4}-.0046122{col 84}{space 3} .0031068
{txt}{space 18}_Icountry_2 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_3 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_4 {c |}{col 31}{res}{space 2} .3028807{col 43}{space 2} .1042542{col 54}{space 1}    2.91{col 63}{space 3}0.004{col 71}{space 4} .0971554{col 84}{space 3}  .508606
{txt}{space 18}_Icountry_5 {c |}{col 31}{res}{space 2}-.0280775{col 43}{space 2} .1110797{col 54}{space 1}   -0.25{col 63}{space 3}0.801{col 71}{space 4}-.2472716{col 84}{space 3} .1911166
{txt}{space 18}_Icountry_6 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_7 {c |}{col 31}{res}{space 2} .0627434{col 43}{space 2} .0982775{col 54}{space 1}    0.64{col 63}{space 3}0.524{col 71}{space 4}-.1311882{col 84}{space 3} .2566749
{txt}{space 18}_Icountry_8 {c |}{col 31}{res}{space 2} .3944372{col 43}{space 2} .1613417{col 54}{space 1}    2.44{col 63}{space 3}0.015{col 71}{space 4} .0760607{col 84}{space 3} .7128137
{txt}{space 18}_Icountry_9 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_10 {c |}{col 31}{res}{space 2} .0677258{col 43}{space 2} .0725249{col 54}{space 1}    0.93{col 63}{space 3}0.352{col 71}{space 4}-.0753879{col 84}{space 3} .2108394
{txt}{space 17}_Icountry_11 {c |}{col 31}{res}{space 2} .3772238{col 43}{space 2} .1409012{col 54}{space 1}    2.68{col 63}{space 3}0.008{col 71}{space 4} .0991827{col 84}{space 3} .6552648
{txt}{space 17}_Icountry_12 {c |}{col 31}{res}{space 2}-.0237854{col 43}{space 2} .1244751{col 54}{space 1}   -0.19{col 63}{space 3}0.849{col 71}{space 4}-.2694129{col 84}{space 3}  .221842
{txt}{space 17}_Icountry_13 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_14 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_15 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_16 {c |}{col 31}{res}{space 2}-.1586588{col 43}{space 2} .0868899{col 54}{space 1}   -1.83{col 63}{space 3}0.070{col 71}{space 4} -.330119{col 84}{space 3} .0128014
{txt}{space 17}_Icountry_17 {c |}{col 31}{res}{space 2} .1316607{col 43}{space 2} .1265264{col 54}{space 1}    1.04{col 63}{space 3}0.299{col 71}{space 4}-.1180146{col 84}{space 3}  .381336
{txt}{space 17}_Icountry_18 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_19 {c |}{col 31}{res}{space 2} .5525812{col 43}{space 2} .1954408{col 54}{space 1}    2.83{col 63}{space 3}0.005{col 71}{space 4} .1669169{col 84}{space 3} .9382456
{txt}{space 17}_Icountry_20 {c |}{col 31}{res}{space 2} .5815205{col 43}{space 2} .1863063{col 54}{space 1}    3.12{col 63}{space 3}0.002{col 71}{space 4} .2138813{col 84}{space 3} .9491596
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} 2.647777{col 43}{space 2} 3.925677{col 54}{space 1}    0.67{col 63}{space 3}0.501{col 71}{space 4}-5.098783{col 84}{space 3} 10.39434
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg Top001incomeshare_ipolate Top001incomeshare_ipolate_lag top_incrate_nl_lag i.country i.year if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
i.year{col 19}_Iyear_1860-2010{col 39}(naturally coded; _Iyear_1860 omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_6 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_13 omitted because of collinearity
note: _Icountry_14 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_18 omitted because of collinearity
note: _Iyear_1865 omitted because of collinearity
note: _Iyear_1870 omitted because of collinearity
note: _Iyear_1875 omitted because of collinearity
note: _Iyear_1880 omitted because of collinearity
note: _Iyear_1885 omitted because of collinearity
note: _Iyear_1890 omitted because of collinearity
note: _Iyear_1895 omitted because of collinearity
note: _Iyear_1905 omitted because of collinearity

Linear regression                               Number of obs     = {res}       194
                                                {txt}F(35, 158)        =  {res}    54.21
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8863
                                                {txt}Root MSE          =    {res} .36105

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}    Top001incomeshare_ipolate{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
Top001incomeshare_ipolate_lag {c |}{col 31}{res}{space 2} .5813404{col 43}{space 2} .1126959{col 54}{space 1}    5.16{col 63}{space 3}0.000{col 71}{space 4} .3587555{col 84}{space 3} .8039252
{txt}{space 11}top_incrate_nl_lag {c |}{col 31}{res}{space 2}-.0068219{col 43}{space 2} .0026516{col 54}{space 1}   -2.57{col 63}{space 3}0.011{col 71}{space 4}-.0120591{col 84}{space 3}-.0015848
{txt}{space 18}_Icountry_2 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_3 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_4 {c |}{col 31}{res}{space 2} .1982976{col 43}{space 2} .0851621{col 54}{space 1}    2.33{col 63}{space 3}0.021{col 71}{space 4} .0300947{col 84}{space 3} .3665005
{txt}{space 18}_Icountry_5 {c |}{col 31}{res}{space 2}-.0447229{col 43}{space 2} .0741141{col 54}{space 1}   -0.60{col 63}{space 3}0.547{col 71}{space 4}-.1911051{col 84}{space 3} .1016593
{txt}{space 18}_Icountry_6 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Icountry_7 {c |}{col 31}{res}{space 2} .0161014{col 43}{space 2} .0931003{col 54}{space 1}    0.17{col 63}{space 3}0.863{col 71}{space 4}-.1677803{col 84}{space 3} .1999832
{txt}{space 18}_Icountry_8 {c |}{col 31}{res}{space 2} .2925115{col 43}{space 2} .1573398{col 54}{space 1}    1.86{col 63}{space 3}0.065{col 71}{space 4} -.018249{col 84}{space 3} .6032721
{txt}{space 18}_Icountry_9 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_10 {c |}{col 31}{res}{space 2}-.0414698{col 43}{space 2} .0792611{col 54}{space 1}   -0.52{col 63}{space 3}0.602{col 71}{space 4}-.1980178{col 84}{space 3} .1150782
{txt}{space 17}_Icountry_11 {c |}{col 31}{res}{space 2} .1924142{col 43}{space 2} .1195938{col 54}{space 1}    1.61{col 63}{space 3}0.110{col 71}{space 4}-.0437945{col 84}{space 3} .4286229
{txt}{space 17}_Icountry_12 {c |}{col 31}{res}{space 2} .0342218{col 43}{space 2} .1021578{col 54}{space 1}    0.33{col 63}{space 3}0.738{col 71}{space 4}-.1675493{col 84}{space 3} .2359929
{txt}{space 17}_Icountry_13 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_14 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_15 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_16 {c |}{col 31}{res}{space 2}-.0772507{col 43}{space 2} .0684867{col 54}{space 1}   -1.13{col 63}{space 3}0.261{col 71}{space 4}-.2125182{col 84}{space 3} .0580168
{txt}{space 17}_Icountry_17 {c |}{col 31}{res}{space 2} .0117109{col 43}{space 2} .0870828{col 54}{space 1}    0.13{col 63}{space 3}0.893{col 71}{space 4}-.1602857{col 84}{space 3} .1837074
{txt}{space 17}_Icountry_18 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 17}_Icountry_19 {c |}{col 31}{res}{space 2} .3040488{col 43}{space 2} .1673688{col 54}{space 1}    1.82{col 63}{space 3}0.071{col 71}{space 4}  -.02652{col 84}{space 3} .6346175
{txt}{space 17}_Icountry_20 {c |}{col 31}{res}{space 2} .4222519{col 43}{space 2} .1603452{col 54}{space 1}    2.63{col 63}{space 3}0.009{col 71}{space 4} .1055554{col 84}{space 3} .7389484
{txt}{space 18}_Iyear_1865 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1870 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1875 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1880 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1885 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1890 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1895 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1900 {c |}{col 31}{res}{space 2} .0948221{col 43}{space 2} .2935043{col 54}{space 1}    0.32{col 63}{space 3}0.747{col 71}{space 4}-.4848759{col 84}{space 3} .6745202
{txt}{space 18}_Iyear_1905 {c |}{col 31}{res}{space 2}        0{col 43}{txt}  (omitted)
{space 18}_Iyear_1910 {c |}{col 31}{res}{space 2} .0137231{col 43}{space 2} .1916364{col 54}{space 1}    0.07{col 63}{space 3}0.943{col 71}{space 4}-.3647765{col 84}{space 3} .3922227
{txt}{space 18}_Iyear_1915 {c |}{col 31}{res}{space 2} .8058682{col 43}{space 2} .3224627{col 54}{space 1}    2.50{col 63}{space 3}0.013{col 71}{space 4} .1689746{col 84}{space 3} 1.442762
{txt}{space 18}_Iyear_1920 {c |}{col 31}{res}{space 2}-.9625737{col 43}{space 2} .4100093{col 54}{space 1}   -2.35{col 63}{space 3}0.020{col 71}{space 4} -1.77238{col 84}{space 3}-.1527676
{txt}{space 18}_Iyear_1925 {c |}{col 31}{res}{space 2}-.3821557{col 43}{space 2} .3148704{col 54}{space 1}   -1.21{col 63}{space 3}0.227{col 71}{space 4}-1.004054{col 84}{space 3} .2397424
{txt}{space 18}_Iyear_1930 {c |}{col 31}{res}{space 2}-.2947038{col 43}{space 2} .2040559{col 54}{space 1}   -1.44{col 63}{space 3}0.151{col 71}{space 4} -.697733{col 84}{space 3} .1083254
{txt}{space 18}_Iyear_1935 {c |}{col 31}{res}{space 2}-.3582778{col 43}{space 2} .2634646{col 54}{space 1}   -1.36{col 63}{space 3}0.176{col 71}{space 4}-.8786446{col 84}{space 3}  .162089
{txt}{space 18}_Iyear_1940 {c |}{col 31}{res}{space 2}-.3841187{col 43}{space 2} .2175727{col 54}{space 1}   -1.77{col 63}{space 3}0.079{col 71}{space 4}-.8138448{col 84}{space 3} .0456073
{txt}{space 18}_Iyear_1945 {c |}{col 31}{res}{space 2}-.8753105{col 43}{space 2} .2621624{col 54}{space 1}   -3.34{col 63}{space 3}0.001{col 71}{space 4}-1.393105{col 84}{space 3}-.3575157
{txt}{space 18}_Iyear_1950 {c |}{col 31}{res}{space 2}-.5353091{col 43}{space 2}  .254776{col 54}{space 1}   -2.10{col 63}{space 3}0.037{col 71}{space 4}-1.038515{col 84}{space 3} -.032103
{txt}{space 18}_Iyear_1955 {c |}{col 31}{res}{space 2}-.5423587{col 43}{space 2} .2598382{col 54}{space 1}   -2.09{col 63}{space 3}0.038{col 71}{space 4}-1.055563{col 84}{space 3}-.0291544
{txt}{space 18}_Iyear_1960 {c |}{col 31}{res}{space 2}-.5750316{col 43}{space 2} .2655761{col 54}{space 1}   -2.17{col 63}{space 3}0.032{col 71}{space 4}-1.099569{col 84}{space 3}-.0504944
{txt}{space 18}_Iyear_1965 {c |}{col 31}{res}{space 2}-.5352367{col 43}{space 2} .2772715{col 54}{space 1}   -1.93{col 63}{space 3}0.055{col 71}{space 4}-1.082873{col 84}{space 3}    .0124
{txt}{space 18}_Iyear_1970 {c |}{col 31}{res}{space 2}-.5937748{col 43}{space 2} .2694621{col 54}{space 1}   -2.20{col 63}{space 3}0.029{col 71}{space 4}-1.125987{col 84}{space 3}-.0615624
{txt}{space 18}_Iyear_1975 {c |}{col 31}{res}{space 2}-.6015069{col 43}{space 2} .2755491{col 54}{space 1}   -2.18{col 63}{space 3}0.031{col 71}{space 4}-1.145742{col 84}{space 3}-.0572721
{txt}{space 18}_Iyear_1980 {c |}{col 31}{res}{space 2}-.5580821{col 43}{space 2} .2738661{col 54}{space 1}   -2.04{col 63}{space 3}0.043{col 71}{space 4}-1.098993{col 84}{space 3}-.0171712
{txt}{space 18}_Iyear_1985 {c |}{col 31}{res}{space 2}-.5283791{col 43}{space 2} .2748267{col 54}{space 1}   -1.92{col 63}{space 3}0.056{col 71}{space 4}-1.071187{col 84}{space 3} .0144289
{txt}{space 18}_Iyear_1990 {c |}{col 31}{res}{space 2}-.2985891{col 43}{space 2} .2772656{col 54}{space 1}   -1.08{col 63}{space 3}0.283{col 71}{space 4}-.8462141{col 84}{space 3} .2490359
{txt}{space 18}_Iyear_1995 {c |}{col 31}{res}{space 2}-.5868294{col 43}{space 2} .2529781{col 54}{space 1}   -2.32{col 63}{space 3}0.022{col 71}{space 4}-1.086485{col 84}{space 3}-.0871743
{txt}{space 18}_Iyear_2000 {c |}{col 31}{res}{space 2}-.1914465{col 43}{space 2} .3132139{col 54}{space 1}   -0.61{col 63}{space 3}0.542{col 71}{space 4}-.8100728{col 84}{space 3} .4271798
{txt}{space 18}_Iyear_2005 {c |}{col 31}{res}{space 2}-.3277245{col 43}{space 2} .2957794{col 54}{space 1}   -1.11{col 63}{space 3}0.270{col 71}{space 4}-.9119162{col 84}{space 3} .2564671
{txt}{space 18}_Iyear_2010 {c |}{col 31}{res}{space 2}-.3533072{col 43}{space 2} .2779285{col 54}{space 1}   -1.27{col 63}{space 3}0.206{col 71}{space 4}-.9022415{col 84}{space 3} .1956271
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} 1.157894{col 43}{space 2} .3313141{col 54}{space 1}    3.49{col 63}{space 3}0.001{col 71}{space 4} .5035181{col 84}{space 3}  1.81227
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * Table 3 
. 
. xi: reg top_inheritance_n top_inheritance_n_lag wealth_ipolate_lag year i.country if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_4 omitted because of collinearity
note: _Icountry_8 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_11 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_16 omitted because of collinearity

Linear regression                               Number of obs     = {res}       212
                                                {txt}F(14, 197)        =  {res}   208.18
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8660
                                                {txt}Root MSE          =    {res} 8.7213

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}    top_inheritance_n{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
top_inheritance_n_lag {c |}{col 23}{res}{space 2} .8970749{col 35}{space 2} .0455441{col 46}{space 1}   19.70{col 55}{space 3}0.000{col 63}{space 4} .8072583{col 76}{space 3} .9868915
{txt}{space 3}wealth_ipolate_lag {c |}{col 23}{res}{space 2}-.0422347{col 35}{space 2} .1308993{col 46}{space 1}   -0.32{col 55}{space 3}0.747{col 63}{space 4}-.3003785{col 76}{space 3} .2159091
{txt}{space 17}year {c |}{col 23}{res}{space 2} -.067499{col 35}{space 2} .0517905{col 46}{space 1}   -1.30{col 55}{space 3}0.194{col 63}{space 4}-.1696339{col 76}{space 3} .0346359
{txt}{space 10}_Icountry_2 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_3 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_4 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_5 {c |}{col 23}{res}{space 2} 1.541234{col 35}{space 2}  2.85081{col 46}{space 1}    0.54{col 55}{space 3}0.589{col 63}{space 4} -4.08079{col 76}{space 3} 7.163257
{txt}{space 10}_Icountry_6 {c |}{col 23}{res}{space 2} .8241723{col 35}{space 2}  2.02492{col 46}{space 1}    0.41{col 55}{space 3}0.684{col 63}{space 4} -3.16913{col 76}{space 3} 4.817475
{txt}{space 10}_Icountry_7 {c |}{col 23}{res}{space 2} 3.178046{col 35}{space 2} 3.373977{col 46}{space 1}    0.94{col 55}{space 3}0.347{col 63}{space 4}-3.475703{col 76}{space 3} 9.831794
{txt}{space 10}_Icountry_8 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_9 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_10 {c |}{col 23}{res}{space 2}-3.360011{col 35}{space 2} 6.270157{col 46}{space 1}   -0.54{col 55}{space 3}0.593{col 63}{space 4}-15.72526{col 76}{space 3} 9.005235
{txt}{space 9}_Icountry_11 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_12 {c |}{col 23}{res}{space 2} 1.286963{col 35}{space 2} 3.094034{col 46}{space 1}    0.42{col 55}{space 3}0.678{col 63}{space 4}-4.814717{col 76}{space 3} 7.388642
{txt}{space 9}_Icountry_13 {c |}{col 23}{res}{space 2}-5.666949{col 35}{space 2} 7.177642{col 46}{space 1}   -0.79{col 55}{space 3}0.431{col 63}{space 4}-19.82183{col 76}{space 3} 8.487928
{txt}{space 9}_Icountry_14 {c |}{col 23}{res}{space 2} 2.271577{col 35}{space 2}  2.94883{col 46}{space 1}    0.77{col 55}{space 3}0.442{col 63}{space 4}-3.543748{col 76}{space 3} 8.086902
{txt}{space 9}_Icountry_15 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_16 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_17 {c |}{col 23}{res}{space 2} 2.094696{col 35}{space 2} 4.038435{col 46}{space 1}    0.52{col 55}{space 3}0.605{col 63}{space 4}-5.869418{col 76}{space 3} 10.05881
{txt}{space 9}_Icountry_18 {c |}{col 23}{res}{space 2}-.3004719{col 35}{space 2} 3.130829{col 46}{space 1}   -0.10{col 55}{space 3}0.924{col 63}{space 4}-6.474715{col 76}{space 3} 5.873771
{txt}{space 9}_Icountry_19 {c |}{col 23}{res}{space 2} 5.718978{col 35}{space 2} 4.667804{col 46}{space 1}    1.23{col 55}{space 3}0.222{col 63}{space 4}-3.486301{col 76}{space 3} 14.92426
{txt}{space 9}_Icountry_20 {c |}{col 23}{res}{space 2} 3.715826{col 35}{space 2} 4.503866{col 46}{space 1}    0.83{col 55}{space 3}0.410{col 63}{space 4}-5.166153{col 76}{space 3} 12.59781
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 134.4871{col 35}{space 2} 103.6714{col 46}{space 1}    1.30{col 55}{space 3}0.196{col 63}{space 4} -69.9611{col 76}{space 3} 338.9353
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg top_inheritance_n top_inheritance_n_lag wealth_ipolate_lag i.country i.year if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
i.year{col 19}_Iyear_1860-2010{col 39}(naturally coded; _Iyear_1860 omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_4 omitted because of collinearity
note: _Icountry_8 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_11 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_16 omitted because of collinearity
note: _Iyear_1865 omitted because of collinearity
note: _Iyear_1870 omitted because of collinearity
note: _Iyear_1875 omitted because of collinearity
note: _Iyear_1880 omitted because of collinearity
note: _Iyear_1885 omitted because of collinearity
note: _Iyear_1890 omitted because of collinearity
note: _Iyear_1895 omitted because of collinearity
note: _Iyear_1980 omitted because of collinearity

Linear regression                               Number of obs     = {res}       212
                                                {txt}F(35, 176)        =  {res}   112.05
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8910
                                                {txt}Root MSE          =    {res} 8.3235

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}    top_inheritance_n{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
top_inheritance_n_lag {c |}{col 23}{res}{space 2} .7797486{col 35}{space 2} .0576856{col 46}{space 1}   13.52{col 55}{space 3}0.000{col 63}{space 4}  .665904{col 76}{space 3} .8935932
{txt}{space 3}wealth_ipolate_lag {c |}{col 23}{res}{space 2}   .00538{col 35}{space 2} .1078673{col 46}{space 1}    0.05{col 55}{space 3}0.960{col 63}{space 4}-.2074999{col 76}{space 3} .2182599
{txt}{space 10}_Icountry_2 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_3 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_4 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_5 {c |}{col 23}{res}{space 2} 1.482418{col 35}{space 2} 2.674877{col 46}{space 1}    0.55{col 55}{space 3}0.580{col 63}{space 4}-3.796544{col 76}{space 3} 6.761379
{txt}{space 10}_Icountry_6 {c |}{col 23}{res}{space 2} .4518907{col 35}{space 2} 2.239415{col 46}{space 1}    0.20{col 55}{space 3}0.840{col 63}{space 4}-3.967672{col 76}{space 3} 4.871453
{txt}{space 10}_Icountry_7 {c |}{col 23}{res}{space 2} 5.602889{col 35}{space 2} 3.424588{col 46}{space 1}    1.64{col 55}{space 3}0.104{col 63}{space 4}-1.155652{col 76}{space 3} 12.36143
{txt}{space 10}_Icountry_8 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_9 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_10 {c |}{col 23}{res}{space 2} .3955265{col 35}{space 2}  6.11684{col 46}{space 1}    0.06{col 55}{space 3}0.949{col 63}{space 4}-11.67627{col 76}{space 3} 12.46732
{txt}{space 9}_Icountry_11 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_12 {c |}{col 23}{res}{space 2} 2.403076{col 35}{space 2} 2.906543{col 46}{space 1}    0.83{col 55}{space 3}0.409{col 63}{space 4}-3.333086{col 76}{space 3} 8.139238
{txt}{space 9}_Icountry_13 {c |}{col 23}{res}{space 2}-3.164422{col 35}{space 2} 5.998379{col 46}{space 1}   -0.53{col 55}{space 3}0.598{col 63}{space 4}-15.00243{col 76}{space 3} 8.673584
{txt}{space 9}_Icountry_14 {c |}{col 23}{res}{space 2} 3.403633{col 35}{space 2} 3.093377{col 46}{space 1}    1.10{col 55}{space 3}0.273{col 63}{space 4}-2.701253{col 76}{space 3} 9.508519
{txt}{space 9}_Icountry_15 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_16 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_17 {c |}{col 23}{res}{space 2} 5.466441{col 35}{space 2} 3.956214{col 46}{space 1}    1.38{col 55}{space 3}0.169{col 63}{space 4}-2.341283{col 76}{space 3} 13.27417
{txt}{space 9}_Icountry_18 {c |}{col 23}{res}{space 2}-2.606193{col 35}{space 2} 3.094524{col 46}{space 1}   -0.84{col 55}{space 3}0.401{col 63}{space 4}-8.713341{col 76}{space 3} 3.500956
{txt}{space 9}_Icountry_19 {c |}{col 23}{res}{space 2} 10.59477{col 35}{space 2} 4.556057{col 46}{space 1}    2.33{col 55}{space 3}0.021{col 63}{space 4} 1.603235{col 76}{space 3} 19.58631
{txt}{space 9}_Icountry_20 {c |}{col 23}{res}{space 2} 9.074869{col 35}{space 2} 4.317818{col 46}{space 1}    2.10{col 55}{space 3}0.037{col 63}{space 4}  .553506{col 76}{space 3} 17.59623
{txt}{space 10}_Iyear_1865 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1870 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1875 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1880 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1885 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1890 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1895 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1900 {c |}{col 23}{res}{space 2}-6.960522{col 35}{space 2} 4.525489{col 46}{space 1}   -1.54{col 55}{space 3}0.126{col 63}{space 4}-15.89173{col 76}{space 3} 1.970686
{txt}{space 10}_Iyear_1905 {c |}{col 23}{res}{space 2}-7.019289{col 35}{space 2} 4.854726{col 46}{space 1}   -1.45{col 55}{space 3}0.150{col 63}{space 4}-16.60026{col 76}{space 3}  2.56168
{txt}{space 10}_Iyear_1910 {c |}{col 23}{res}{space 2}-5.057973{col 35}{space 2} 4.761286{col 46}{space 1}   -1.06{col 55}{space 3}0.290{col 63}{space 4}-14.45454{col 76}{space 3}  4.33859
{txt}{space 10}_Iyear_1915 {c |}{col 23}{res}{space 2}-4.581226{col 35}{space 2} 4.668717{col 46}{space 1}   -0.98{col 55}{space 3}0.328{col 63}{space 4} -13.7951{col 76}{space 3} 4.632648
{txt}{space 10}_Iyear_1920 {c |}{col 23}{res}{space 2} 5.148137{col 35}{space 2} 5.049313{col 46}{space 1}    1.02{col 55}{space 3}0.309{col 63}{space 4}-4.816857{col 76}{space 3} 15.11313
{txt}{space 10}_Iyear_1925 {c |}{col 23}{res}{space 2}-.3775391{col 35}{space 2}  3.97334{col 46}{space 1}   -0.10{col 55}{space 3}0.924{col 63}{space 4}-8.219062{col 76}{space 3} 7.463983
{txt}{space 10}_Iyear_1930 {c |}{col 23}{res}{space 2}-2.359455{col 35}{space 2} 5.394053{col 46}{space 1}   -0.44{col 55}{space 3}0.662{col 63}{space 4} -13.0048{col 76}{space 3} 8.285895
{txt}{space 10}_Iyear_1935 {c |}{col 23}{res}{space 2} 5.512748{col 35}{space 2} 4.557185{col 46}{space 1}    1.21{col 55}{space 3}0.228{col 63}{space 4}-3.481013{col 76}{space 3} 14.50651
{txt}{space 10}_Iyear_1940 {c |}{col 23}{res}{space 2} 5.356838{col 35}{space 2} 4.212343{col 46}{space 1}    1.27{col 55}{space 3}0.205{col 63}{space 4}-2.956367{col 76}{space 3} 13.67004
{txt}{space 10}_Iyear_1945 {c |}{col 23}{res}{space 2} 3.210239{col 35}{space 2} 3.380982{col 46}{space 1}    0.95{col 55}{space 3}0.344{col 63}{space 4}-3.462245{col 76}{space 3} 9.882722
{txt}{space 10}_Iyear_1950 {c |}{col 23}{res}{space 2} 8.351398{col 35}{space 2} 4.654311{col 46}{space 1}    1.79{col 55}{space 3}0.074{col 63}{space 4}-.8340445{col 76}{space 3} 17.53684
{txt}{space 10}_Iyear_1955 {c |}{col 23}{res}{space 2} 3.099478{col 35}{space 2} 3.039232{col 46}{space 1}    1.02{col 55}{space 3}0.309{col 63}{space 4}-2.898551{col 76}{space 3} 9.097507
{txt}{space 10}_Iyear_1960 {c |}{col 23}{res}{space 2}  1.60558{col 35}{space 2} 3.574045{col 46}{space 1}    0.45{col 55}{space 3}0.654{col 63}{space 4}-5.447921{col 76}{space 3} 8.659081
{txt}{space 10}_Iyear_1965 {c |}{col 23}{res}{space 2} 2.099282{col 35}{space 2} 3.064475{col 46}{space 1}    0.69{col 55}{space 3}0.494{col 63}{space 4}-3.948564{col 76}{space 3} 8.147129
{txt}{space 10}_Iyear_1970 {c |}{col 23}{res}{space 2} 3.982693{col 35}{space 2} 2.954366{col 46}{space 1}    1.35{col 55}{space 3}0.179{col 63}{space 4} -1.84785{col 76}{space 3} 9.813235
{txt}{space 10}_Iyear_1975 {c |}{col 23}{res}{space 2} 4.115421{col 35}{space 2} 3.285568{col 46}{space 1}    1.25{col 55}{space 3}0.212{col 63}{space 4}-2.368761{col 76}{space 3}  10.5996
{txt}{space 10}_Iyear_1980 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1985 {c |}{col 23}{res}{space 2} 1.493197{col 35}{space 2} 4.348025{col 46}{space 1}    0.34{col 55}{space 3}0.732{col 63}{space 4} -7.08778{col 76}{space 3} 10.07417
{txt}{space 10}_Iyear_1990 {c |}{col 23}{res}{space 2}-.7256067{col 35}{space 2} 3.491072{col 46}{space 1}   -0.21{col 55}{space 3}0.836{col 63}{space 4}-7.615357{col 76}{space 3} 6.164144
{txt}{space 10}_Iyear_1995 {c |}{col 23}{res}{space 2}-2.683168{col 35}{space 2} 3.927388{col 46}{space 1}   -0.68{col 55}{space 3}0.495{col 63}{space 4}  -10.434{col 76}{space 3} 5.067668
{txt}{space 10}_Iyear_2000 {c |}{col 23}{res}{space 2}   1.1121{col 35}{space 2} 2.939217{col 46}{space 1}    0.38{col 55}{space 3}0.706{col 63}{space 4}-4.688545{col 76}{space 3} 6.912745
{txt}{space 10}_Iyear_2005 {c |}{col 23}{res}{space 2}-5.501772{col 35}{space 2} 4.604493{col 46}{space 1}   -1.19{col 55}{space 3}0.234{col 63}{space 4} -14.5889{col 76}{space 3} 3.585354
{txt}{space 10}_Iyear_2010 {c |}{col 23}{res}{space 2}-7.155404{col 35}{space 2}  6.21022{col 46}{space 1}   -1.15{col 55}{space 3}0.251{col 63}{space 4}-19.41149{col 76}{space 3} 5.100678
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 1.025233{col 35}{space 2} 4.308703{col 46}{space 1}    0.24{col 55}{space 3}0.812{col 63}{space 4} -7.47814{col 76}{space 3} 9.528606
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg wealth_ipolate wealth_ipolate_lag top_inheritance_n_lag year i.country if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_4 omitted because of collinearity
note: _Icountry_8 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_11 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_16 omitted because of collinearity

Linear regression                               Number of obs     = {res}       206
                                                {txt}{help j_robustsingular:F(13, 191) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.9669
                                                {txt}Root MSE          =    {res} 2.5375

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}       wealth_ipolate{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}wealth_ipolate_lag {c |}{col 23}{res}{space 2} .9016056{col 35}{space 2} .0263152{col 46}{space 1}   34.26{col 55}{space 3}0.000{col 63}{space 4} .8496999{col 76}{space 3} .9535114
{txt}top_inheritance_n_lag {c |}{col 23}{res}{space 2}-.0411446{col 35}{space 2} .0125269{col 46}{space 1}   -3.28{col 55}{space 3}0.001{col 63}{space 4}-.0658534{col 76}{space 3}-.0164358
{txt}{space 17}year {c |}{col 23}{res}{space 2}-.0091644{col 35}{space 2} .0116162{col 46}{space 1}   -0.79{col 55}{space 3}0.431{col 63}{space 4}-.0320769{col 76}{space 3} .0137482
{txt}{space 10}_Icountry_2 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_3 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_4 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_5 {c |}{col 23}{res}{space 2} 1.908278{col 35}{space 2} .9202776{col 46}{space 1}    2.07{col 55}{space 3}0.039{col 63}{space 4} .0930656{col 76}{space 3} 3.723491
{txt}{space 10}_Icountry_6 {c |}{col 23}{res}{space 2} 1.313232{col 35}{space 2} .6829384{col 46}{space 1}    1.92{col 55}{space 3}0.056{col 63}{space 4}-.0338379{col 76}{space 3} 2.660302
{txt}{space 10}_Icountry_7 {c |}{col 23}{res}{space 2} 2.327147{col 35}{space 2} .8382598{col 46}{space 1}    2.78{col 55}{space 3}0.006{col 63}{space 4} .6737111{col 76}{space 3} 3.980582
{txt}{space 10}_Icountry_8 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_9 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_10 {c |}{col 23}{res}{space 2} 2.575813{col 35}{space 2} .9723227{col 46}{space 1}    2.65{col 55}{space 3}0.009{col 63}{space 4} .6579438{col 76}{space 3} 4.493683
{txt}{space 9}_Icountry_11 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_12 {c |}{col 23}{res}{space 2} 1.970587{col 35}{space 2} .8171946{col 46}{space 1}    2.41{col 55}{space 3}0.017{col 63}{space 4} .3587021{col 76}{space 3} 3.582472
{txt}{space 9}_Icountry_13 {c |}{col 23}{res}{space 2} .0988629{col 35}{space 2}  .728183{col 46}{space 1}    0.14{col 55}{space 3}0.892{col 63}{space 4} -1.33745{col 76}{space 3} 1.535176
{txt}{space 9}_Icountry_14 {c |}{col 23}{res}{space 2} 1.960402{col 35}{space 2} .6007971{col 46}{space 1}    3.26{col 55}{space 3}0.001{col 63}{space 4} .7753522{col 76}{space 3} 3.145451
{txt}{space 9}_Icountry_15 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_16 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_17 {c |}{col 23}{res}{space 2}  2.34629{col 35}{space 2} .8260904{col 46}{space 1}    2.84{col 55}{space 3}0.005{col 63}{space 4} .7168577{col 76}{space 3} 3.975722
{txt}{space 9}_Icountry_18 {c |}{col 23}{res}{space 2} 1.550402{col 35}{space 2} 1.029247{col 46}{space 1}    1.51{col 55}{space 3}0.134{col 63}{space 4}-.4797476{col 76}{space 3} 3.580552
{txt}{space 9}_Icountry_19 {c |}{col 23}{res}{space 2} 3.507928{col 35}{space 2} 1.036249{col 46}{space 1}    3.39{col 55}{space 3}0.001{col 63}{space 4} 1.463966{col 76}{space 3}  5.55189
{txt}{space 9}_Icountry_20 {c |}{col 23}{res}{space 2} 4.504881{col 35}{space 2} .8911118{col 46}{space 1}    5.06{col 55}{space 3}0.000{col 63}{space 4} 2.747197{col 76}{space 3} 6.262565
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 18.88574{col 35}{space 2} 23.03518{col 46}{space 1}    0.82{col 55}{space 3}0.413{col 63}{space 4}-26.55028{col 76}{space 3} 64.32175
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. xi: reg wealth_ipolate wealth_ipolate_lag top_inheritance_n_lag i.country i.year if year>=1900 & year<=2010, robust
{txt}i.country{col 19}_Icountry_1-20{col 39}(_Icountry_1 for cou~y==Australia omitted)
i.year{col 19}_Iyear_1860-2010{col 39}(naturally coded; _Iyear_1860 omitted)
note: _Icountry_2 omitted because of collinearity
note: _Icountry_3 omitted because of collinearity
note: _Icountry_4 omitted because of collinearity
note: _Icountry_8 omitted because of collinearity
note: _Icountry_9 omitted because of collinearity
note: _Icountry_11 omitted because of collinearity
note: _Icountry_15 omitted because of collinearity
note: _Icountry_16 omitted because of collinearity
note: _Iyear_1865 omitted because of collinearity
note: _Iyear_1870 omitted because of collinearity
note: _Iyear_1875 omitted because of collinearity
note: _Iyear_1880 omitted because of collinearity
note: _Iyear_1885 omitted because of collinearity
note: _Iyear_1890 omitted because of collinearity
note: _Iyear_1895 omitted because of collinearity
note: _Iyear_1910 omitted because of collinearity

Linear regression                               Number of obs     = {res}       206
                                                {txt}{help j_robustsingular:F(34, 170) }       =  {res}        .
                                                {txt}Prob > F          = {res}         .
                                                {txt}R-squared         = {res}    0.9750
                                                {txt}Root MSE          =    {res} 2.3389

{txt}{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}       wealth_ipolate{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}wealth_ipolate_lag {c |}{col 23}{res}{space 2} .9039817{col 35}{space 2} .0298906{col 46}{space 1}   30.24{col 55}{space 3}0.000{col 63}{space 4}  .844977{col 76}{space 3} .9629863
{txt}top_inheritance_n_lag {c |}{col 23}{res}{space 2}-.0061898{col 35}{space 2} .0143692{col 46}{space 1}   -0.43{col 55}{space 3}0.667{col 63}{space 4}-.0345548{col 76}{space 3} .0221753
{txt}{space 10}_Icountry_2 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_3 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_4 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_5 {c |}{col 23}{res}{space 2} 1.704231{col 35}{space 2} .9388358{col 46}{space 1}    1.82{col 55}{space 3}0.071{col 63}{space 4}-.1490468{col 76}{space 3} 3.557508
{txt}{space 10}_Icountry_6 {c |}{col 23}{res}{space 2} 1.367603{col 35}{space 2} .7290779{col 46}{space 1}    1.88{col 55}{space 3}0.062{col 63}{space 4}-.0716087{col 76}{space 3} 2.806815
{txt}{space 10}_Icountry_7 {c |}{col 23}{res}{space 2} 1.322202{col 35}{space 2} .8860414{col 46}{space 1}    1.49{col 55}{space 3}0.137{col 63}{space 4}-.4268584{col 76}{space 3} 3.071262
{txt}{space 10}_Icountry_8 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Icountry_9 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_10 {c |}{col 23}{res}{space 2} 1.383748{col 35}{space 2} 1.007114{col 46}{space 1}    1.37{col 55}{space 3}0.171{col 63}{space 4}-.6043122{col 76}{space 3} 3.371808
{txt}{space 9}_Icountry_11 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_12 {c |}{col 23}{res}{space 2}  1.33274{col 35}{space 2} .8808059{col 46}{space 1}    1.51{col 55}{space 3}0.132{col 63}{space 4} -.405986{col 76}{space 3} 3.071465
{txt}{space 9}_Icountry_13 {c |}{col 23}{res}{space 2}-.7853403{col 35}{space 2} .9028528{col 46}{space 1}   -0.87{col 55}{space 3}0.386{col 63}{space 4}-2.567587{col 76}{space 3} .9969061
{txt}{space 9}_Icountry_14 {c |}{col 23}{res}{space 2} 1.433852{col 35}{space 2} .7264948{col 46}{space 1}    1.97{col 55}{space 3}0.050{col 63}{space 4}-.0002604{col 76}{space 3} 2.867965
{txt}{space 9}_Icountry_15 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_16 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 9}_Icountry_17 {c |}{col 23}{res}{space 2} 1.040651{col 35}{space 2} .8895562{col 46}{space 1}    1.17{col 55}{space 3}0.244{col 63}{space 4} -.715348{col 76}{space 3}  2.79665
{txt}{space 9}_Icountry_18 {c |}{col 23}{res}{space 2} 1.925114{col 35}{space 2} 1.085687{col 46}{space 1}    1.77{col 55}{space 3}0.078{col 63}{space 4}-.2180506{col 76}{space 3} 4.068279
{txt}{space 9}_Icountry_19 {c |}{col 23}{res}{space 2} 1.586323{col 35}{space 2} 1.221682{col 46}{space 1}    1.30{col 55}{space 3}0.196{col 63}{space 4}-.8252975{col 76}{space 3} 3.997943
{txt}{space 9}_Icountry_20 {c |}{col 23}{res}{space 2}  2.69505{col 35}{space 2} 1.096687{col 46}{space 1}    2.46{col 55}{space 3}0.015{col 63}{space 4} .5301705{col 76}{space 3} 4.859929
{txt}{space 10}_Iyear_1865 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1870 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1875 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1880 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1885 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1890 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1895 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1900 {c |}{col 23}{res}{space 2} .3721655{col 35}{space 2} 1.206537{col 46}{space 1}    0.31{col 55}{space 3}0.758{col 63}{space 4}-2.009558{col 76}{space 3} 2.753889
{txt}{space 10}_Iyear_1905 {c |}{col 23}{res}{space 2}-.0644126{col 35}{space 2} .9746064{col 46}{space 1}   -0.07{col 55}{space 3}0.947{col 63}{space 4}-1.988302{col 76}{space 3} 1.859477
{txt}{space 10}_Iyear_1910 {c |}{col 23}{res}{space 2}        0{col 35}{txt}  (omitted)
{space 10}_Iyear_1915 {c |}{col 23}{res}{space 2}-2.163255{col 35}{space 2} .9896627{col 46}{space 1}   -2.19{col 55}{space 3}0.030{col 63}{space 4}-4.116866{col 76}{space 3}-.2096444
{txt}{space 10}_Iyear_1920 {c |}{col 23}{res}{space 2}-4.775638{col 35}{space 2} 1.302772{col 46}{space 1}   -3.67{col 55}{space 3}0.000{col 63}{space 4}-7.347333{col 76}{space 3}-2.203944
{txt}{space 10}_Iyear_1925 {c |}{col 23}{res}{space 2}-1.502382{col 35}{space 2} .9220159{col 46}{space 1}   -1.63{col 55}{space 3}0.105{col 63}{space 4}-3.322457{col 76}{space 3} .3176931
{txt}{space 10}_Iyear_1930 {c |}{col 23}{res}{space 2}-2.007568{col 35}{space 2}  .882947{col 46}{space 1}   -2.27{col 55}{space 3}0.024{col 63}{space 4} -3.75052{col 76}{space 3}-.2646159
{txt}{space 10}_Iyear_1935 {c |}{col 23}{res}{space 2}-5.138428{col 35}{space 2} 1.261047{col 46}{space 1}   -4.07{col 55}{space 3}0.000{col 63}{space 4}-7.627756{col 76}{space 3}-2.649101
{txt}{space 10}_Iyear_1940 {c |}{col 23}{res}{space 2} -2.99519{col 35}{space 2} 1.138235{col 46}{space 1}   -2.63{col 55}{space 3}0.009{col 63}{space 4}-5.242085{col 76}{space 3}-.7482961
{txt}{space 10}_Iyear_1945 {c |}{col 23}{res}{space 2}-5.025298{col 35}{space 2} 1.030874{col 46}{space 1}   -4.87{col 55}{space 3}0.000{col 63}{space 4}-7.060261{col 76}{space 3}-2.990334
{txt}{space 10}_Iyear_1950 {c |}{col 23}{res}{space 2}-5.192285{col 35}{space 2} 1.286516{col 46}{space 1}   -4.04{col 55}{space 3}0.000{col 63}{space 4}-7.731888{col 76}{space 3}-2.652681
{txt}{space 10}_Iyear_1955 {c |}{col 23}{res}{space 2}-3.717047{col 35}{space 2}  1.34325{col 46}{space 1}   -2.77{col 55}{space 3}0.006{col 63}{space 4}-6.368646{col 76}{space 3}-1.065448
{txt}{space 10}_Iyear_1960 {c |}{col 23}{res}{space 2}-4.671768{col 35}{space 2}   1.5411{col 46}{space 1}   -3.03{col 55}{space 3}0.003{col 63}{space 4}-7.713924{col 76}{space 3}-1.629611
{txt}{space 10}_Iyear_1965 {c |}{col 23}{res}{space 2}-4.798855{col 35}{space 2} 1.263091{col 46}{space 1}   -3.80{col 55}{space 3}0.000{col 63}{space 4}-7.292219{col 76}{space 3}-2.305492
{txt}{space 10}_Iyear_1970 {c |}{col 23}{res}{space 2}-4.779817{col 35}{space 2} 1.280891{col 46}{space 1}   -3.73{col 55}{space 3}0.000{col 63}{space 4}-7.308317{col 76}{space 3}-2.251316
{txt}{space 10}_Iyear_1975 {c |}{col 23}{res}{space 2}-5.145245{col 35}{space 2}  1.29847{col 46}{space 1}   -3.96{col 55}{space 3}0.000{col 63}{space 4}-7.708447{col 76}{space 3}-2.582044
{txt}{space 10}_Iyear_1980 {c |}{col 23}{res}{space 2}-4.488877{col 35}{space 2} 1.292798{col 46}{space 1}   -3.47{col 55}{space 3}0.001{col 63}{space 4}-7.040882{col 76}{space 3}-1.936872
{txt}{space 10}_Iyear_1985 {c |}{col 23}{res}{space 2}-3.803262{col 35}{space 2} 1.258409{col 46}{space 1}   -3.02{col 55}{space 3}0.003{col 63}{space 4}-6.287383{col 76}{space 3}-1.319141
{txt}{space 10}_Iyear_1990 {c |}{col 23}{res}{space 2}-3.518145{col 35}{space 2} 1.308578{col 46}{space 1}   -2.69{col 55}{space 3}0.008{col 63}{space 4}-6.101299{col 76}{space 3}-.9349909
{txt}{space 10}_Iyear_1995 {c |}{col 23}{res}{space 2}-3.348628{col 35}{space 2} 1.400947{col 46}{space 1}   -2.39{col 55}{space 3}0.018{col 63}{space 4}-6.114121{col 76}{space 3}-.5831352
{txt}{space 10}_Iyear_2000 {c |}{col 23}{res}{space 2}-2.952368{col 35}{space 2} 2.173544{col 46}{space 1}   -1.36{col 55}{space 3}0.176{col 63}{space 4} -7.24298{col 76}{space 3} 1.338244
{txt}{space 10}_Iyear_2005 {c |}{col 23}{res}{space 2}-3.666848{col 35}{space 2} 1.348363{col 46}{space 1}   -2.72{col 55}{space 3}0.007{col 63}{space 4}-6.328538{col 76}{space 3}-1.005157
{txt}{space 10}_Iyear_2010 {c |}{col 23}{res}{space 2}-3.857239{col 35}{space 2} 1.333089{col 46}{space 1}   -2.89{col 55}{space 3}0.004{col 63}{space 4}-6.488778{col 76}{space 3}  -1.2257
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} 4.410232{col 35}{space 2} 1.428707{col 46}{space 1}    3.09{col 55}{space 3}0.002{col 63}{space 4} 1.589941{col 76}{space 3} 7.230524
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. clear all
{res}{txt}
{com}. 
. /**
> German Survey Analysis: Figure 1a; Figure 2a; Table 4; Table A.1 
> **/
. 
. use "STAN0117_DE_OUTPUT.dta", clear
{txt}
{com}. 
. /****
> Variable and global variable construction
> *****/
. 
. gen female=0
{txt}
{com}. replace female=1 if gender==2
{txt}(1,074 real changes made)

{com}. 
. gen age=2019-birthyr
{txt}
{com}. 
. gen age1834 = cond(age >= 18 & age <= 34, 1, 0)
{txt}
{com}. gen age3554 = cond(age >= 35 & age <= 54, 1, 0)
{txt}
{com}. gen agegt55 = cond(age > 55, 1, 0)
{txt}
{com}. 
. label var female "Female"
{txt}
{com}. label var age "Age"
{txt}
{com}. label var educ_de "Education"
{txt}
{com}. 
. gen universityEduc=0
{txt}
{com}. replace universityEduc=1 if educ_de>=7
{txt}(518 real changes made)

{com}. 
. ren Q26 indiv_inc
{res}{txt}
{com}. 
. rename Bracket5 linearTaxOver250k 
{res}{txt}
{com}. 
. rename Q72 equal_treat  
{res}{txt}
{com}. label variable equal_treat "Should government treat citizens equally?"
{txt}
{com}. recode equal_treat 1=5 2=4 3=3 4=2 5=1
{txt}(equal_treat: 1341 changes made)

{com}. label define equal_treat_lbl    1 "Treat citizens differently" ///
>                                                                         2 "2" ///
>                                                                         3 "3" ///
>                                                                         4 "4" ///
>                                                                         5 "Treat citizens equally", replace
{txt}
{com}. label values equal_treat equal_treat_lbl
{txt}
{com}. 
. gen treatEqualdi = cond(equal_treat >= 3, 1, 0)
{txt}
{com}. 
. rename Q31 cons_ec_ideology
{res}{txt}
{com}. recode cons_ec_ideology 1=5 2=4 3=3 4=2 5=1
{txt}(cons_ec_ideology: 924 changes made)

{com}. label variable cons_ec_ideology "Economic ideological self-identification"
{txt}
{com}. label define ideology_lbl       1 "Very conservative" ///
>                                                                 2 "Conservative " ///
>                                                                 3 "Moderate" ///
>                                                                 4 "Progressive" ///
>                                                                 5 "Very Progressive", replace
{txt}
{com}. label values cons_ec_ideology ideology_lbl
{txt}
{com}. 
. gen CDUCSUsupporter=0
{txt}
{com}. replace CDUCSUsupporter=1 if Q29==1 & Q30==1
{txt}(263 real changes made)

{com}. 
. tab CDUCSUsupporter

{txt}CDUCSUsuppo {c |}
       rter {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}      1,837       87.48       87.48
{txt}          1 {c |}{res}        263       12.52      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      2,100      100.00
{txt}
{com}. 
. rename Q54 work_luck
{res}{txt}
{com}. label variable work_luck "Work hard or lucky to get ahead?"
{txt}
{com}. label define work_luck_lbl 1 "Hard work is most important" ///
>         2 "Hard work & luck are equally important" ///
>         3 "Luck is the most important", replace
{txt}
{com}. label values work_luck work_luck_lbl
{txt}
{com}. 
. gen hardwork=1 if work_luck==1
{txt}(1,930 missing values generated)

{com}. replace hardwork=0 if work_luck==2|work_luck==3
{txt}(1,930 real changes made)

{com}. 
. ren Q51 problemIneq
{res}{txt}
{com}. label define problemIneq_lbl    1 "Not a problem" ///
>                                                                 2 "A small problem" ///
>                                                                 3 "A problem" ///
>                                                                 4 "A serious problem" ///
>                                                                 5 "A very serious problem", replace
{txt}
{com}. label values problemIneq problemIneq_lbl
{txt}
{com}. 
. gen age1830=0
{txt}
{com}. replace age1830=1 if age>=18 & age<=30
{txt}(403 real changes made)

{com}. gen age3150=0
{txt}
{com}. replace age3150=1 if age>=31 & age<=50
{txt}(589 real changes made)

{com}. gen age5165=0
{txt}
{com}. replace age5165=1 if age>=51 & age<=65
{txt}(590 real changes made)

{com}. gen agegt65=0
{txt}
{com}. replace agegt65=1 if age>65
{txt}(518 real changes made)

{com}. 
. 
. * Figure 1a 
. hist equal_treat, start(1) d percent xtitle(Equal Treatment) bcolor(navy) xlabel(1(1)5) graphregion(color(white))
{txt}(start={res}1{txt}, width={res}1{txt})
{res}{txt}
{com}. graph export de_main_equal_hist.pdf, replace
{txt}(file de_main_equal_hist.pdf written in PDF format)

{com}. 
. * Figure 2a 
. heatplot equal_treat problemIneq, discrete ytitle(Equal Treatment) xtitle(Inequality a Problem) xlabel(1(1)5) ylabel(1(1)5) colors(hcl, blues reverse) keylabels(,f(%12.2f)) graphregion(color(white))
{res}{txt}
{com}. graph export de_main_equal_ineq_heat.pdf, replace
{txt}(file de_main_equal_ineq_heat.pdf written in PDF format)

{com}. 
. * Table 4
. 
. reg linearTaxOver250k equal_treat [pweight=weight], robust
{txt}(sum of wgt is 2,100.00000000001)

Linear regression                               Number of obs     = {res}     2,100
                                                {txt}F(1, 2098)        =  {res}    18.63
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0142
                                                {txt}Root MSE          =    {res} 20.422

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}linearT~250k{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}equal_treat {c |}{col 14}{res}{space 2}-1.977983{col 26}{space 2} .4582848{col 37}{space 1}   -4.32{col 46}{space 3}0.000{col 54}{space 4}-2.876723{col 67}{space 3}-1.079243
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 55.76099{col 26}{space 2} 1.428114{col 37}{space 1}   39.05{col 46}{space 3}0.000{col 54}{space 4} 52.96032{col 67}{space 3} 58.56165
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver250k equal_treat female age3150 age5165 agegt65 universityEduc indiv_inc [pweight=weight], robust
{txt}(sum of wgt is 2,100.00000000001)

Linear regression                               Number of obs     = {res}     2,100
                                                {txt}F(7, 2092)        =  {res}     6.75
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0282
                                                {txt}Root MSE          =    {res} 20.307

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~250k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-2.013413{col 28}{space 2} .4527002{col 39}{space 1}   -4.45{col 48}{space 3}0.000{col 56}{space 4}-2.901203{col 69}{space 3}-1.125623
{txt}{space 8}female {c |}{col 16}{res}{space 2}-2.993322{col 28}{space 2} 1.092231{col 39}{space 1}   -2.74{col 48}{space 3}0.006{col 56}{space 4}-5.135295{col 69}{space 3}-.8513498
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.935792{col 28}{space 2} 1.835413{col 39}{space 1}    1.05{col 48}{space 3}0.292{col 56}{space 4}-1.663634{col 69}{space 3} 5.535218
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} 2.477249{col 28}{space 2} 1.810672{col 39}{space 1}    1.37{col 48}{space 3}0.171{col 56}{space 4}-1.073658{col 69}{space 3} 6.028155
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 2.947015{col 28}{space 2} 1.923007{col 39}{space 1}    1.53{col 48}{space 3}0.126{col 56}{space 4}-.8241916{col 69}{space 3} 6.718222
{txt}universityEduc {c |}{col 16}{res}{space 2} 2.287366{col 28}{space 2} 1.066208{col 39}{space 1}    2.15{col 48}{space 3}0.032{col 56}{space 4} .1964268{col 69}{space 3} 4.378305
{txt}{space 5}indiv_inc {c |}{col 16}{res}{space 2}  .155989{col 28}{space 2} .1401145{col 39}{space 1}    1.11{col 48}{space 3}0.266{col 56}{space 4}-.1187895{col 69}{space 3} .4307674
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 53.70273{col 28}{space 2} 2.454156{col 39}{space 1}   21.88{col 48}{space 3}0.000{col 56}{space 4} 48.88989{col 69}{space 3} 58.51557
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver250k equal_treat female age3150 age5165 agegt65 universityEduc indiv_inc  cons_ec_ideology [pweight=weight], robust
{txt}(sum of wgt is 2,100.00000000001)

Linear regression                               Number of obs     = {res}     2,100
                                                {txt}F(8, 2091)        =  {res}     8.00
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0376
                                                {txt}Root MSE          =    {res} 20.212

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}linearTaxOv~250k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}equal_treat {c |}{col 18}{res}{space 2} -1.89668{col 30}{space 2} .4547558{col 41}{space 1}   -4.17{col 50}{space 3}0.000{col 58}{space 4}-2.788501{col 71}{space 3}-1.004858
{txt}{space 10}female {c |}{col 18}{res}{space 2} -3.26049{col 30}{space 2} 1.088761{col 41}{space 1}   -2.99{col 50}{space 3}0.003{col 58}{space 4}-5.395659{col 71}{space 3}-1.125321
{txt}{space 9}age3150 {c |}{col 18}{res}{space 2} 2.381196{col 30}{space 2} 1.833293{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4}-1.214073{col 71}{space 3} 5.976466
{txt}{space 9}age5165 {c |}{col 18}{res}{space 2} 2.526679{col 30}{space 2} 1.803139{col 41}{space 1}    1.40{col 50}{space 3}0.161{col 58}{space 4}-1.009456{col 71}{space 3} 6.062815
{txt}{space 9}agegt65 {c |}{col 18}{res}{space 2} 3.098323{col 30}{space 2} 1.917362{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.6618148{col 71}{space 3} 6.858461
{txt}{space 2}universityEduc {c |}{col 18}{res}{space 2} 1.934054{col 30}{space 2} 1.062958{col 41}{space 1}    1.82{col 50}{space 3}0.069{col 58}{space 4}-.1505115{col 71}{space 3} 4.018619
{txt}{space 7}indiv_inc {c |}{col 18}{res}{space 2} .2013343{col 30}{space 2} .1402347{col 41}{space 1}    1.44{col 50}{space 3}0.151{col 58}{space 4}-.0736798{col 71}{space 3} .4763485
{txt}cons_ec_ideology {c |}{col 18}{res}{space 2}-2.829152{col 30}{space 2} .6856808{col 41}{space 1}   -4.13{col 50}{space 3}0.000{col 58}{space 4} -4.17384{col 71}{space 3}-1.484464
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 61.43716{col 30}{space 2} 2.812155{col 41}{space 1}   21.85{col 50}{space 3}0.000{col 58}{space 4} 55.92224{col 71}{space 3} 66.95207
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver250k equal_treat female age3150 age5165 agegt65 universityEduc indiv_inc  CDUCSUsupporter [pweight=weight], robust
{txt}(sum of wgt is 2,100.00000000001)

Linear regression                               Number of obs     = {res}     2,100
                                                {txt}F(8, 2091)        =  {res}     6.16
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0302
                                                {txt}Root MSE          =    {res} 20.291

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}linearTaxO~250k{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}equal_treat {c |}{col 17}{res}{space 2}-2.001924{col 29}{space 2} .4514393{col 40}{space 1}   -4.43{col 49}{space 3}0.000{col 57}{space 4}-2.887241{col 70}{space 3}-1.116606
{txt}{space 9}female {c |}{col 17}{res}{space 2}-3.041721{col 29}{space 2} 1.090098{col 40}{space 1}   -2.79{col 49}{space 3}0.005{col 57}{space 4}-5.179511{col 70}{space 3}-.9039306
{txt}{space 8}age3150 {c |}{col 17}{res}{space 2} 2.082582{col 29}{space 2} 1.831119{col 40}{space 1}    1.14{col 49}{space 3}0.256{col 57}{space 4}-1.508423{col 70}{space 3} 5.673587
{txt}{space 8}age5165 {c |}{col 17}{res}{space 2} 2.636383{col 29}{space 2} 1.809401{col 40}{space 1}    1.46{col 49}{space 3}0.145{col 57}{space 4} -.912031{col 70}{space 3} 6.184797
{txt}{space 8}agegt65 {c |}{col 17}{res}{space 2}  3.32185{col 29}{space 2} 1.940045{col 40}{space 1}    1.71{col 49}{space 3}0.087{col 57}{space 4}-.4827698{col 70}{space 3}  7.12647
{txt}{space 1}universityEduc {c |}{col 17}{res}{space 2} 2.327981{col 29}{space 2} 1.066521{col 40}{space 1}    2.18{col 49}{space 3}0.029{col 57}{space 4} .2364269{col 70}{space 3} 4.419535
{txt}{space 6}indiv_inc {c |}{col 17}{res}{space 2} .1840246{col 29}{space 2} .1416417{col 40}{space 1}    1.30{col 49}{space 3}0.194{col 57}{space 4}-.0937488{col 70}{space 3}  .461798
{txt}CDUCSUsupporter {c |}{col 17}{res}{space 2}-2.501587{col 29}{space 2} 1.477626{col 40}{space 1}   -1.69{col 49}{space 3}0.091{col 57}{space 4}-5.399358{col 70}{space 3} .3961833
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 53.76754{col 29}{space 2} 2.438771{col 40}{space 1}   22.05{col 49}{space 3}0.000{col 57}{space 4} 48.98487{col 70}{space 3} 58.55022
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver250k equal_treat female age3150 age5165 agegt65 universityEduc indiv_inc  hardwork [pweight=weight], robust
{txt}(sum of wgt is 2,100.00000000001)

Linear regression                               Number of obs     = {res}     2,100
                                                {txt}F(8, 2091)        =  {res}     5.92
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0282
                                                {txt}Root MSE          =    {res} 20.312

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~250k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-2.013248{col 28}{space 2} .4507925{col 39}{space 1}   -4.47{col 48}{space 3}0.000{col 56}{space 4}-2.897297{col 69}{space 3}-1.129199
{txt}{space 8}female {c |}{col 16}{res}{space 2}-2.993618{col 28}{space 2} 1.088209{col 39}{space 1}   -2.75{col 48}{space 3}0.006{col 56}{space 4}-5.127704{col 69}{space 3}-.8595326
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.935455{col 28}{space 2} 1.838521{col 39}{space 1}    1.05{col 48}{space 3}0.293{col 56}{space 4}-1.670066{col 69}{space 3} 5.540976
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} 2.476445{col 28}{space 2} 1.818795{col 39}{space 1}    1.36{col 48}{space 3}0.173{col 56}{space 4}-1.090392{col 69}{space 3} 6.043282
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 2.945956{col 28}{space 2}  1.93099{col 39}{space 1}    1.53{col 48}{space 3}0.127{col 56}{space 4}-.8409066{col 69}{space 3} 6.732819
{txt}universityEduc {c |}{col 16}{res}{space 2} 2.287476{col 28}{space 2} 1.066921{col 39}{space 1}    2.14{col 48}{space 3}0.032{col 56}{space 4} .1951375{col 69}{space 3} 4.379815
{txt}{space 5}indiv_inc {c |}{col 16}{res}{space 2}   .15606{col 28}{space 2} .1412863{col 39}{space 1}    1.10{col 48}{space 3}0.269{col 56}{space 4}-.1210165{col 69}{space 3} .4331364
{txt}{space 6}hardwork {c |}{col 16}{res}{space 2} -.013106{col 28}{space 2} 2.048639{col 39}{space 1}   -0.01{col 48}{space 3}0.995{col 56}{space 4} -4.03069{col 69}{space 3} 4.004478
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}  53.7037{col 28}{space 2} 2.460601{col 39}{space 1}   21.83{col 48}{space 3}0.000{col 56}{space 4} 48.87822{col 69}{space 3} 58.52918
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver250k equal_treat female age3150 age5165 agegt65 universityEduc indiv_inc  problemIneq [pweight=weight], robust
{txt}(sum of wgt is 2,100.00000000001)

Linear regression                               Number of obs     = {res}     2,100
                                                {txt}F(8, 2091)        =  {res}     7.79
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0401
                                                {txt}Root MSE          =    {res} 20.186

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~250k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-1.793311{col 28}{space 2} .4452451{col 39}{space 1}   -4.03{col 48}{space 3}0.000{col 56}{space 4}-2.666481{col 69}{space 3}-.9201414
{txt}{space 8}female {c |}{col 16}{res}{space 2}-2.746497{col 28}{space 2} 1.083855{col 39}{space 1}   -2.53{col 48}{space 3}0.011{col 56}{space 4}-4.872045{col 69}{space 3}-.6209486
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.357767{col 28}{space 2} 1.839084{col 39}{space 1}    0.74{col 48}{space 3}0.460{col 56}{space 4}-2.248858{col 69}{space 3} 4.964393
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2}  1.52941{col 28}{space 2} 1.830429{col 39}{space 1}    0.84{col 48}{space 3}0.404{col 56}{space 4}-2.060242{col 69}{space 3} 5.119062
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 2.191755{col 28}{space 2} 1.941142{col 39}{space 1}    1.13{col 48}{space 3}0.259{col 56}{space 4}-1.615018{col 69}{space 3} 5.998527
{txt}universityEduc {c |}{col 16}{res}{space 2} 2.488279{col 28}{space 2} 1.059049{col 39}{space 1}    2.35{col 48}{space 3}0.019{col 56}{space 4} .4113799{col 69}{space 3} 4.565179
{txt}{space 5}indiv_inc {c |}{col 16}{res}{space 2} .2351096{col 28}{space 2} .1400032{col 39}{space 1}    1.68{col 48}{space 3}0.093{col 56}{space 4}-.0394507{col 69}{space 3} .5096698
{txt}{space 3}problemIneq {c |}{col 16}{res}{space 2} 2.279183{col 28}{space 2} .5680417{col 39}{space 1}    4.01{col 48}{space 3}0.000{col 56}{space 4} 1.165196{col 69}{space 3} 3.393169
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 44.86395{col 28}{space 2} 3.061045{col 39}{space 1}   14.66{col 48}{space 3}0.000{col 56}{space 4} 38.86094{col 69}{space 3} 50.86696
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * Table A.1
. 
. sum female age1830 age3150 age5165 agegt65 universityEduc

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}female {c |}{res}      2,100    .5114286    .4999884          0          1
{txt}{space 5}age1830 {c |}{res}      2,100    .1919048    .3938924          0          1
{txt}{space 5}age3150 {c |}{res}      2,100    .2804762    .4493389          0          1
{txt}{space 5}age5165 {c |}{res}      2,100    .2809524    .4495713          0          1
{txt}{space 5}agegt65 {c |}{res}      2,100    .2466667    .4311737          0          1
{txt}{hline 13}{c +}{hline 57}
university~c {c |}{res}      2,100    .2466667    .4311737          0          1
{txt}
{com}. svyset caseid [pweight=weight]

      {txt}pweight:{col 16}{res}weight
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}{res}caseid
        {txt}FPC 1:{col 16}<zero>
{p2colreset}{...}

{com}. svy: mean female age1830 age3150 age5165 agegt65 universityEduc
{res}{txt}(running {bf:mean} on estimation sample)
{res}
{txt}Survey: Mean estimation

{col 1}Number of strata{col 18}= {res}      1{txt}{col 37}Number of obs{col 53}= {res}     2,100
{txt}{col 1}Number of PSUs{col 18}= {res}  2,100{txt}{col 37}Population size{col 53}={res}      2,100
{txt}{col 37}Design df{col 53}= {res}     2,099

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}{col 28}  Linearized
{col 16}{c |}       Mean{col 28}   Std. Err.{col 40}     [95% Con{col 53}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}female {c |}{col 16}{res}{space 2}  .508999{col 28}{space 2} .0134582{col 39}{space 5} .4826061{col 53}{space 3} .5353919
{txt}{space 7}age1830 {c |}{col 16}{res}{space 2} .1900003{col 28}{space 2} .0129008{col 39}{space 5} .1647006{col 53}{space 3}    .2153
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} .2555602{col 28}{space 2} .0111795{col 39}{space 5} .2336362{col 53}{space 3} .2774842
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} .3096676{col 28}{space 2} .0119692{col 39}{space 5} .2861948{col 53}{space 3} .3331404
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} .2447719{col 28}{space 2} .0108205{col 39}{space 5} .2235519{col 53}{space 3} .2659919
{txt}universityEduc {c |}{col 16}{res}{space 2} .3559241{col 28}{space 2} .0131212{col 39}{space 5} .3301922{col 53}{space 3}  .381656
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. clear all
{res}{txt}
{com}. 
. /**
> UK Survey Analysis: Figure 1b; Figure 2b; Table 5; Table A.2 
> **/
. 
. use "UK full survey (indiv, with contextual data).dta", clear
{txt}
{com}. 
. /****
> Variable and global variable construction
> *****/
. gen controlprime=0  
{txt}
{com}. replace controlprime=1 if treats==1
{txt}(486 real changes made)

{com}. 
. gen defenseprime=0  
{txt}
{com}. replace defenseprime=1 if treats==2
{txt}(478 real changes made)

{com}. 
. gen welfareprime=0  
{txt}
{com}. replace welfareprime=1 if treats==3
{txt}(482 real changes made)

{com}. 
. gen higheredprime=0  
{txt}
{com}. replace higheredprime=1 if treats==4
{txt}(467 real changes made)

{com}. 
. gen age1834 = cond(age >= 18 & age <= 34, 1, 0)
{txt}
{com}. gen age3554 = cond(age >= 35 & age <= 54, 1, 0)
{txt}
{com}. gen agegt55 = cond(age > 55, 1, 0)
{txt}
{com}. 
. gen noQual = cond(educ == 1, 1, 0) if educ != .
{txt}(64 missing values generated)

{com}. gen otherQual = cond(educ >= 2 & educ <= 10, 1, 0) if educ != .
{txt}(64 missing values generated)

{com}. gen alvl = cond(educ == 11 | educ == 12, 1, 0) if educ != .
{txt}(64 missing values generated)

{com}. gen grads = cond(educ >= 15 & educ <= 18, 1, 0) if educ != .
{txt}(64 missing values generated)

{com}. 
. label var female "Female"
{txt}
{com}. label var age "Age"
{txt}
{com}. label var educ "Education"
{txt}
{com}. label var isMarried "Married"
{txt}
{com}. label var pcnuk2015 "% non-UK born"
{txt}
{com}. label var changedPC "Has moved"
{txt}
{com}. label var hh_inc "HH income"
{txt}
{com}. label var workingClass "Working Class"
{txt}
{com}. label var middleClass "Middle Class"
{txt}
{com}. 
. rename q18 taxOver150k  
{res}{txt}
{com}. gen linearTaxOver150k = .
{txt}(1,913 missing values generated)

{com}. replace linearTax = 0 if taxOver150k == 1
{txt}(6 real changes made)

{com}. replace linearTax = 5 if taxOver150k == 2
{txt}(12 real changes made)

{com}. replace linearTax = 10 if taxOver150k == 3
{txt}(21 real changes made)

{com}. replace linearTax = 15 if taxOver150k == 4
{txt}(17 real changes made)

{com}. replace linearTax = 20 if taxOver150k == 5
{txt}(61 real changes made)

{com}. replace linearTax = 25 if taxOver150k == 6
{txt}(85 real changes made)

{com}. replace linearTax = 30 if taxOver150k == 7
{txt}(120 real changes made)

{com}. replace linearTax = 35 if taxOver150k == 8
{txt}(107 real changes made)

{com}. replace linearTax = 40 if taxOver150k == 9
{txt}(438 real changes made)

{com}. replace linearTax = 50 if taxOver150k == 10
{txt}(719 real changes made)

{com}. replace linearTax = 60 if taxOver150k == 11
{txt}(264 real changes made)

{com}. replace linearTax = 70 if taxOver150k == 12
{txt}(31 real changes made)

{com}. replace linearTax = 80 if taxOver150k == 13
{txt}(32 real changes made)

{com}. 
. rename q31 equal_treat  
{res}{txt}
{com}. label variable equal_treat "Should government treat citizens equally?"
{txt}
{com}. recode equal_treat 1=5 2=4 3=3 4=2 5=1
{txt}(equal_treat: 1350 changes made)

{com}. label define equal_treat_lbl    1 "Treat citizens differently" ///
>                                                                         2 "2" ///
>                                                                         3 "3" ///
>                                                                         4 "4" ///
>                                                                         5 "Treat citizens equally", replace
{txt}
{com}. label values equal_treat equal_treat_lbl
{txt}
{com}. 
. gen treatEqualdi = cond(equal_treat >= 3, 1, 0)
{txt}
{com}. 
. rename rightwing right_ideology
{res}{txt}
{com}. replace right_ideology=right_ideology + 1
{txt}(1,913 real changes made)

{com}. label variable right_ideology "Ideological self-identification"
{txt}
{com}. label define ideology_lbl       1 "Left" ///
>                                                                 2 "2" ///
>                                                                 3 "3" ///
>                                                                 4 "4" ///
>                                                                 5 "5" ///
>                                                                 6 "6" ///
>                                                                 7 "7" ///
>                                                                 8 "8" ///
>                                                                 9 "9" ///
>                                                                 10 "10" ///
>                                                                 11 "Right", replace
{txt}
{com}. label values right_ideology ideology_lbl
{txt}
{com}. 
. rename q33 work_luck
{res}{txt}
{com}. label variable work_luck "Work hard or lucky to get ahead?"
{txt}
{com}. label define work_luck_lbl 1 "Hard work is most important" ///
>         2 "Hard work & luck are equally important" ///
>         3 "Luck is the most important", replace
{txt}
{com}. label values work_luck work_luck_lbl
{txt}
{com}. 
. gen hardwork=1 if work_luck==1
{txt}(1,363 missing values generated)

{com}. replace hardwork=0 if work_luck==2|work_luck==3
{txt}(1,363 real changes made)

{com}. 
. gen reduceIneq = .
{txt}(1,913 missing values generated)

{com}. replace reduceIneq = 1 if q49 == 2 & q50 == 1
{txt}(22 real changes made)

{com}. replace reduceIneq = 2 if q49 == 2 & q50 == 2
{txt}(62 real changes made)

{com}. replace reduceIneq = 3 if q49 == 2 & q50 == 3
{txt}(15 real changes made)

{com}. replace reduceIneq = 4 if q49 == 3
{txt}(554 real changes made)

{com}. replace reduceIneq = 5 if q49 == 1 & q50 == 3
{txt}(104 real changes made)

{com}. replace reduceIneq = 6 if q49 == 1 & q50 == 2
{txt}(599 real changes made)

{com}. replace reduceIneq = 7 if q49 == 1 & q50 == 1
{txt}(557 real changes made)

{com}. gen ineqAverse = cond(reduceIneq > 4, 1, 0) if reduceIneq != .
{txt}
{com}. 
. 
. rename q47 govtsvcs
{res}{txt}
{com}. label variable govtsvcs "Should the government provide more, fewer, or the same # of services as it does now?"
{txt}note: label truncated to 80 characters

{com}. label define more_fewer_same_lbl 1 "More" 2 "Fewer" 3 "Same", replace
{txt}
{com}. label values govtsvcs more_fewer_same_lbl
{txt}
{com}. 
. rename q48 govtsvcs_preflvl
{res}{txt}
{com}. label variable govtsvcs_preflvl "If govt should provide more/fewer services, how much?"
{txt}
{com}. label define scale_lot_slightly 1 "A lot" 2 "Somewhat" 3 "Slightly", replace
{txt}
{com}. label values govtsvcs_preflvl scale_lot_slightly
{txt}
{com}. 
. gen moregovtservices7=.
{txt}(1,913 missing values generated)

{com}. replace moregovtservices7=1 if govtsvcs==2 & govtsvcs_preflvl==1
{txt}(29 real changes made)

{com}. replace moregovtservices7=2 if govtsvcs==2 & govtsvcs_preflvl==2
{txt}(82 real changes made)

{com}. replace moregovtservices7=3 if govtsvcs==2 & govtsvcs_preflvl==3
{txt}(57 real changes made)

{com}. replace moregovtservices7=4 if govtsvcs==3
{txt}(748 real changes made)

{com}. replace moregovtservices7=5 if govtsvcs==1 & govtsvcs_preflvl==3
{txt}(128 real changes made)

{com}. replace moregovtservices7=6 if govtsvcs==1 & govtsvcs_preflvl==2
{txt}(477 real changes made)

{com}. replace moregovtservices7=7 if govtsvcs==1 & govtsvcs_preflvl==1
{txt}(392 real changes made)

{com}. label variable moregovtservices7 "Should the government provide more, fewer, or the same # of services as it does now?"
{txt}note: label truncated to 80 characters

{com}. label define moregovtservices7_lbl 1 "A lot fewer" 2 "somewhat fewer" 3 "slighter fewer" 4 "same" 5 "slightly more" 6 "somewhat more" 7 "a lot more", replace
{txt}
{com}. label values moregovtservices7 moregovtservices7_lbl
{txt}
{com}. 
. gen cons_id=0
{txt}
{com}. replace cons_id=1 if partyPref==1
{txt}(410 real changes made)

{com}. 
. gen lab_id=0
{txt}
{com}. replace lab_id=1 if partyPref==2
{txt}(549 real changes made)

{com}. 
. gen age1830=0
{txt}
{com}. replace age1830=1 if age>=18 & age<=30
{txt}(364 real changes made)

{com}. replace age3150=0
{txt}(656 real changes made)

{com}. replace age3150=1 if age>=31 & age<=50
{txt}(656 real changes made)

{com}. gen age5165=0
{txt}
{com}. replace age5165=1 if age>=51 & age<=65
{txt}(481 real changes made)

{com}. gen agegt65=0
{txt}
{com}. replace agegt65=1 if age>65
{txt}(412 real changes made)

{com}. 
. * Figure 1b 
. hist equal_treat, start(1) d percent xtitle(Equal Treatment) bcolor(navy) xlabel(1(1)5) ylabel(0(10)40) graphregion(color(white))
{txt}(start={res}1{txt}, width={res}1{txt})
{res}{txt}
{com}. graph export uk_main_equal_hist.pdf, replace
{txt}(file uk_main_equal_hist.pdf written in PDF format)

{com}. 
. * Figure 2b 
. heatplot equal_treat reduceIneq, discrete ytitle(Equal Treatment) xtitle(Reduce Inequality) xlabel(1(1)7) ylabel(1(1)5) colors(hcl, blues reverse) keylabels(,f(%12.2f)) graphregion(color(white))
{res}{txt}
{com}. graph export uk_main_equal_ineq_heat.pdf, replace
{txt}(file uk_main_equal_ineq_heat.pdf written in PDF format)

{com}. 
. * Table 5
. reg linearTaxOver150k equal_treat [pweight=weight], robust
{txt}(sum of wgt is 1,912.99999851562)

Linear regression                               Number of obs     = {res}     1,913
                                                {txt}F(1, 1911)        =  {res}    16.91
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0138
                                                {txt}Root MSE          =    {res} 13.417

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}linearT~150k{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}equal_treat {c |}{col 14}{res}{space 2} -1.24332{col 26}{space 2} .3023668{col 37}{space 1}   -4.11{col 46}{space 3}0.000{col 54}{space 4}-1.836323{col 67}{space 3}-.6503161
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 47.76053{col 26}{space 2} .9434999{col 37}{space 1}   50.62{col 46}{space 3}0.000{col 54}{space 4} 45.91013{col 67}{space 3} 49.61092
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc [pweight=weight], robust
{txt}(sum of wgt is 1,263.60166646827)

Linear regression                               Number of obs     = {res}     1,246
                                                {txt}F(7, 1238)        =  {res}     3.96
                                                {txt}Prob > F          = {res}    0.0003
                                                {txt}R-squared         = {res}    0.0327
                                                {txt}Root MSE          =    {res} 12.843

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~150k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-1.260725{col 28}{space 2} .3637208{col 39}{space 1}   -3.47{col 48}{space 3}0.001{col 56}{space 4}-1.974302{col 69}{space 3}-.5471475
{txt}{space 8}female {c |}{col 16}{res}{space 2}-1.419588{col 28}{space 2} .8725922{col 39}{space 1}   -1.63{col 48}{space 3}0.104{col 56}{space 4}-3.131511{col 69}{space 3} .2923351
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.550311{col 28}{space 2} 1.519156{col 39}{space 1}    1.02{col 48}{space 3}0.308{col 56}{space 4}-1.430095{col 69}{space 3} 4.530716
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} 2.736933{col 28}{space 2} 1.576914{col 39}{space 1}    1.74{col 48}{space 3}0.083{col 56}{space 4} -.356787{col 69}{space 3} 5.830653
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 2.602787{col 28}{space 2} 1.615691{col 39}{space 1}    1.61{col 48}{space 3}0.107{col 56}{space 4}-.5670077{col 69}{space 3} 5.772583
{txt}universityEduc {c |}{col 16}{res}{space 2}   2.0736{col 28}{space 2} .8297808{col 39}{space 1}    2.50{col 48}{space 3}0.013{col 56}{space 4} .4456677{col 69}{space 3} 3.701532
{txt}{space 8}hh_inc {c |}{col 16}{res}{space 2} .1577333{col 28}{space 2} .1262622{col 39}{space 1}    1.25{col 48}{space 3}0.212{col 56}{space 4}-.0899782{col 69}{space 3} .4054448
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 44.77231{col 28}{space 2} 2.194442{col 39}{space 1}   20.40{col 48}{space 3}0.000{col 56}{space 4} 40.46708{col 69}{space 3} 49.07755
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  right_ideology [pweight=weight], robust
{txt}(sum of wgt is 1,263.60166646827)

Linear regression                               Number of obs     = {res}     1,246
                                                {txt}F(8, 1237)        =  {res}     8.92
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0613
                                                {txt}Root MSE          =    {res} 12.657

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~150k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-1.168624{col 28}{space 2} .3681007{col 39}{space 1}   -3.17{col 48}{space 3}0.002{col 56}{space 4}-1.890794{col 69}{space 3}-.4464531
{txt}{space 8}female {c |}{col 16}{res}{space 2}-1.660455{col 28}{space 2} .8660071{col 39}{space 1}   -1.92{col 48}{space 3}0.055{col 56}{space 4} -3.35946{col 69}{space 3} .0385499
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.805048{col 28}{space 2}  1.50645{col 39}{space 1}    1.20{col 48}{space 3}0.231{col 56}{space 4}-1.150431{col 69}{space 3} 4.760527
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} 3.215687{col 28}{space 2} 1.567838{col 39}{space 1}    2.05{col 48}{space 3}0.040{col 56}{space 4} .1397721{col 69}{space 3} 6.291602
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 4.033272{col 28}{space 2} 1.613465{col 39}{space 1}    2.50{col 48}{space 3}0.013{col 56}{space 4} .8678409{col 69}{space 3} 7.198703
{txt}universityEduc {c |}{col 16}{res}{space 2} 1.588991{col 28}{space 2}  .822306{col 39}{space 1}    1.93{col 48}{space 3}0.054{col 56}{space 4}-.0242781{col 69}{space 3} 3.202259
{txt}{space 8}hh_inc {c |}{col 16}{res}{space 2} .1849045{col 28}{space 2} .1236105{col 39}{space 1}    1.50{col 48}{space 3}0.135{col 56}{space 4} -.057605{col 69}{space 3} .4274139
{txt}right_ideology {c |}{col 16}{res}{space 2}-1.072451{col 28}{space 2} .2224912{col 39}{space 1}   -4.82{col 48}{space 3}0.000{col 56}{space 4}-1.508953{col 69}{space 3}-.6359488
{txt}{space 9}_cons {c |}{col 16}{res}{space 2}  50.4204{col 28}{space 2} 2.360136{col 39}{space 1}   21.36{col 48}{space 3}0.000{col 56}{space 4} 45.79008{col 69}{space 3} 55.05071
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  cons_id [pweight=weight], robust
{txt}(sum of wgt is 1,263.60166646827)

Linear regression                               Number of obs     = {res}     1,246
                                                {txt}F(8, 1237)        =  {res}     4.84
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0388
                                                {txt}Root MSE          =    {res} 12.808

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~150k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-1.195063{col 28}{space 2}  .366185{col 39}{space 1}   -3.26{col 48}{space 3}0.001{col 56}{space 4}-1.913475{col 69}{space 3}-.4766502
{txt}{space 8}female {c |}{col 16}{res}{space 2}-1.457672{col 28}{space 2} .8687183{col 39}{space 1}   -1.68{col 48}{space 3}0.094{col 56}{space 4}-3.161996{col 69}{space 3} .2466518
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.569735{col 28}{space 2} 1.507258{col 39}{space 1}    1.04{col 48}{space 3}0.298{col 56}{space 4} -1.38733{col 69}{space 3} 4.526799
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} 3.056134{col 28}{space 2} 1.571932{col 39}{space 1}    1.94{col 48}{space 3}0.052{col 56}{space 4}-.0278134{col 69}{space 3} 6.140081
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 3.443994{col 28}{space 2}   1.5945{col 39}{space 1}    2.16{col 48}{space 3}0.031{col 56}{space 4} .3157706{col 69}{space 3} 6.572217
{txt}universityEduc {c |}{col 16}{res}{space 2} 1.896358{col 28}{space 2} .8281886{col 39}{space 1}    2.29{col 48}{space 3}0.022{col 56}{space 4} .2715485{col 69}{space 3} 3.521168
{txt}{space 8}hh_inc {c |}{col 16}{res}{space 2} .1986877{col 28}{space 2}  .125213{col 39}{space 1}    1.59{col 48}{space 3}0.113{col 56}{space 4}-.0469657{col 69}{space 3} .4443411
{txt}{space 7}cons_id {c |}{col 16}{res}{space 2}-2.541548{col 28}{space 2} .8980696{col 39}{space 1}   -2.83{col 48}{space 3}0.005{col 56}{space 4}-4.303456{col 69}{space 3}-.7796398
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 44.72752{col 28}{space 2}  2.17816{col 39}{space 1}   20.53{col 48}{space 3}0.000{col 56}{space 4} 40.45422{col 69}{space 3} 49.00081
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  hardwork [pweight=weight], robust
{txt}(sum of wgt is 1,263.60166646827)

Linear regression                               Number of obs     = {res}     1,246
                                                {txt}F(8, 1237)        =  {res}     5.01
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0475
                                                {txt}Root MSE          =    {res}  12.75

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~150k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-1.162493{col 28}{space 2} .3619638{col 39}{space 1}   -3.21{col 48}{space 3}0.001{col 56}{space 4}-1.872624{col 69}{space 3}-.4523622
{txt}{space 8}female {c |}{col 16}{res}{space 2}-1.350544{col 28}{space 2} .8606562{col 39}{space 1}   -1.57{col 48}{space 3}0.117{col 56}{space 4}-3.039051{col 69}{space 3} .3379631
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.396927{col 28}{space 2} 1.488492{col 39}{space 1}    0.94{col 48}{space 3}0.348{col 56}{space 4}-1.523321{col 69}{space 3} 4.317175
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} 2.501669{col 28}{space 2} 1.546248{col 39}{space 1}    1.62{col 48}{space 3}0.106{col 56}{space 4}-.5318886{col 69}{space 3} 5.535227
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 2.300361{col 28}{space 2} 1.578129{col 39}{space 1}    1.46{col 48}{space 3}0.145{col 56}{space 4}-.7957448{col 69}{space 3} 5.396467
{txt}universityEduc {c |}{col 16}{res}{space 2}  1.88137{col 28}{space 2} .8240321{col 39}{space 1}    2.28{col 48}{space 3}0.023{col 56}{space 4} .2647145{col 69}{space 3} 3.498025
{txt}{space 8}hh_inc {c |}{col 16}{res}{space 2} .1591301{col 28}{space 2} .1248788{col 39}{space 1}    1.27{col 48}{space 3}0.203{col 56}{space 4}-.0858676{col 69}{space 3} .4041278
{txt}{space 6}hardwork {c |}{col 16}{res}{space 2}-3.494063{col 28}{space 2} .9934525{col 39}{space 1}   -3.52{col 48}{space 3}0.000{col 56}{space 4}-5.443101{col 69}{space 3}-1.545025
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 45.71271{col 28}{space 2} 2.082862{col 39}{space 1}   21.95{col 48}{space 3}0.000{col 56}{space 4} 41.62637{col 69}{space 3} 49.79904
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  reduceIneq [pweight=weight], robust
{txt}(sum of wgt is 1,263.60166646827)

Linear regression                               Number of obs     = {res}     1,246
                                                {txt}F(8, 1237)        =  {res}    11.49
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0978
                                                {txt}Root MSE          =    {res} 12.408

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 16}{c |}{col 28}    Robust
{col 1}linearTax~150k{col 16}{c |}      Coef.{col 28}   Std. Err.{col 40}      t{col 48}   P>|t|{col 56}     [95% Con{col 69}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 3}equal_treat {c |}{col 16}{res}{space 2}-.9998195{col 28}{space 2} .3366142{col 39}{space 1}   -2.97{col 48}{space 3}0.003{col 56}{space 4}-1.660217{col 69}{space 3}-.3394216
{txt}{space 8}female {c |}{col 16}{res}{space 2}-1.030491{col 28}{space 2} .8284082{col 39}{space 1}   -1.24{col 48}{space 3}0.214{col 56}{space 4}-2.655732{col 69}{space 3} .5947494
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} 1.694159{col 28}{space 2} 1.416163{col 39}{space 1}    1.20{col 48}{space 3}0.232{col 56}{space 4}-1.084188{col 69}{space 3} 4.472506
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2} 3.100551{col 28}{space 2} 1.481283{col 39}{space 1}    2.09{col 48}{space 3}0.037{col 56}{space 4} .1944457{col 69}{space 3} 6.006657
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} 3.103284{col 28}{space 2}  1.50711{col 39}{space 1}    2.06{col 48}{space 3}0.040{col 56}{space 4} .1465089{col 69}{space 3}  6.06006
{txt}universityEduc {c |}{col 16}{res}{space 2} 1.233249{col 28}{space 2} .8062369{col 39}{space 1}    1.53{col 48}{space 3}0.126{col 56}{space 4}-.3484939{col 69}{space 3} 2.814992
{txt}{space 8}hh_inc {c |}{col 16}{res}{space 2} .2051419{col 28}{space 2} .1175013{col 39}{space 1}    1.75{col 48}{space 3}0.081{col 56}{space 4}-.0253819{col 69}{space 3} .4356657
{txt}{space 4}reduceIneq {c |}{col 16}{res}{space 2} 2.346909{col 28}{space 2}  .305236{col 39}{space 1}    7.69{col 48}{space 3}0.000{col 56}{space 4} 1.748072{col 69}{space 3} 2.945747
{txt}{space 9}_cons {c |}{col 16}{res}{space 2} 30.77951{col 28}{space 2} 2.644595{col 39}{space 1}   11.64{col 48}{space 3}0.000{col 56}{space 4} 25.59112{col 69}{space 3} 35.96789
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * Table A.2
. 
. sum female age1830 age3150 age5165 agegt65 universityEduc 

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}female {c |}{res}      1,913    .5426032    .4983119          0          1
{txt}{space 5}age1830 {c |}{res}      1,913    .1902771    .3926223          0          1
{txt}{space 5}age3150 {c |}{res}      1,913    .3429169    .4748081          0          1
{txt}{space 5}age5165 {c |}{res}      1,913    .2514375    .4339529          0          1
{txt}{space 5}agegt65 {c |}{res}      1,913    .2153685    .4111852          0          1
{txt}{hline 13}{c +}{hline 57}
university~c {c |}{res}      1,849     .453218    .4979413          0          1
{txt}
{com}. svyset caseid [pweight=weight]

      {txt}pweight:{col 16}{res}weight
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}{res}caseid
        {txt}FPC 1:{col 16}<zero>
{p2colreset}{...}

{com}. svy: mean female age1830 age3150 age5165 agegt65 universityEduc 
{res}{txt}(running {bf:mean} on estimation sample)
{res}
{txt}Survey: Mean estimation

{col 1}Number of strata{col 18}= {res}      1{txt}{col 37}Number of obs{col 53}= {res}     1,849
{txt}{col 1}Number of PSUs{col 18}= {res}  1,849{txt}{col 37}Population size{col 53}={res} 1,836.3538
{txt}{col 37}Design df{col 53}= {res}     1,848

{txt}{hline 15}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 16}{c |}{col 28}  Linearized
{col 16}{c |}       Mean{col 28}   Std. Err.{col 40}     [95% Con{col 53}f. Interval]
{hline 15}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 8}female {c |}{col 16}{res}{space 2} .5087862{col 28}{space 2} .0134231{col 39}{space 5} .4824601{col 53}{space 3} .5351122
{txt}{space 7}age1830 {c |}{col 16}{res}{space 2} .2186402{col 28}{space 2} .0128463{col 39}{space 5} .1934453{col 53}{space 3}  .243835
{txt}{space 7}age3150 {c |}{col 16}{res}{space 2} .3476173{col 28}{space 2} .0124549{col 39}{space 5} .3231901{col 53}{space 3} .3720445
{txt}{space 7}age5165 {c |}{col 16}{res}{space 2}  .221841{col 28}{space 2}  .010118{col 39}{space 5} .2019971{col 53}{space 3}  .241685
{txt}{space 7}agegt65 {c |}{col 16}{res}{space 2} .2119015{col 28}{space 2} .0106349{col 39}{space 5} .1910437{col 53}{space 3} .2327592
{txt}universityEduc {c |}{col 16}{res}{space 2}  .401455{col 28}{space 2} .0126816{col 39}{space 5} .3765832{col 53}{space 3} .4263269
{txt}{hline 15}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. clear all
{res}{txt}
{com}. 
. /**
> US Experimental Survey Analysis: Table 6; Table 7; Table A.3
> **/
. 
. use CCES18_NYU_OUTPUT.DTA, replace
{txt}
{com}. 
. /****
> Variable and global variable construction
> *****/
. 
. gen EqualTreatExpos=0
{txt}
{com}. replace EqualTreatExpos=1 if IMAGES_rand==1
{txt}(516 real changes made)

{com}. 
. gen ProgTaxQ_first=0
{txt}
{com}. replace ProgTaxQ_first=1 if NYU345_347_rand==1
{txt}(514 real changes made)

{com}. 
. gen ProgTaxOrder=NYU345
{txt}(3 missing values generated)

{com}. 
. gen ProgTaxD1=.
{txt}(1,000 missing values generated)

{com}. replace ProgTaxD1=0 if NYU345==1
{txt}(279 real changes made)

{com}. replace ProgTaxD1=1 if NYU345==2
{txt}(464 real changes made)

{com}. replace ProgTaxD1=1 if NYU345==3
{txt}(254 real changes made)

{com}. 
. gen ProgTaxD2=.
{txt}(1,000 missing values generated)

{com}. replace ProgTaxD2=0 if NYU345==1
{txt}(279 real changes made)

{com}. replace ProgTaxD2=0 if NYU345==2
{txt}(464 real changes made)

{com}. replace ProgTaxD2=1 if NYU345==3
{txt}(254 real changes made)

{com}. 
. gen equal_treat=.
{txt}(1,000 missing values generated)

{com}. replace equal_treat=1 if NYU346==5
{txt}(114 real changes made)

{com}. replace equal_treat=2 if NYU346==4
{txt}(231 real changes made)

{com}. replace equal_treat=3 if NYU346==3
{txt}(205 real changes made)

{com}. replace equal_treat=4 if NYU346==2
{txt}(121 real changes made)

{com}. replace equal_treat=5 if NYU346==1
{txt}(304 real changes made)

{com}. 
. gen HardWork=0
{txt}
{com}. replace HardWork=1 if NYU347==1
{txt}(469 real changes made)

{com}. 
. gen female=0
{txt}
{com}. replace female=1 if gender==2
{txt}(574 real changes made)

{com}. 
. gen somecollege=0
{txt}
{com}. replace somecollege=1 if educ==3
{txt}(234 real changes made)

{com}. replace somecollege=1 if educ==4
{txt}(94 real changes made)

{com}. 
. gen college4degplus=0
{txt}
{com}. replace college4degplus=1 if educ==5
{txt}(232 real changes made)

{com}. replace college4degplus=1 if educ==6
{txt}(147 real changes made)

{com}. 
. gen black=0
{txt}
{com}. replace black=1 if race==2
{txt}(94 real changes made)

{com}. 
. gen hisp=0
{txt}
{com}. replace hisp=1 if race==3
{txt}(84 real changes made)

{com}. 
. gen othermin=0
{txt}
{com}. replace othermin=1 if race==4
{txt}(26 real changes made)

{com}. replace othermin=1 if race==5
{txt}(7 real changes made)

{com}. replace othermin=1 if race==6
{txt}(28 real changes made)

{com}. replace othermin=1 if race==7
{txt}(11 real changes made)

{com}. replace othermin=1 if race==8
{txt}(2 real changes made)

{com}. 
. gen faminc2=faminc_new
{txt}(6 missing values generated)

{com}. replace faminc2=. if faminc_new==97
{txt}(93 real changes made, 93 to missing)

{com}. 
. gen age=2018-birthyr
{txt}
{com}. gen age1830=0
{txt}
{com}. replace age1830=1 if age>=18 & age<=30
{txt}(223 real changes made)

{com}. gen age3150=0
{txt}
{com}. replace age3150=1 if age>=31 & age<=50
{txt}(308 real changes made)

{com}. gen age5165=0
{txt}
{com}. replace age5165=1 if age>=51 & age<=65
{txt}(273 real changes made)

{com}. gen agegt65=0
{txt}
{com}. replace agegt65=1 if age>65
{txt}(196 real changes made)

{com}. 
. gen constolibideo=.
{txt}(1,000 missing values generated)

{com}. replace constolibideo=1 if CC18_334A==7
{txt}(107 real changes made)

{com}. replace constolibideo=2 if CC18_334A==6
{txt}(163 real changes made)

{com}. replace constolibideo=3 if CC18_334A==5
{txt}(96 real changes made)

{com}. replace constolibideo=4 if CC18_334A==4
{txt}(235 real changes made)

{com}. replace constolibideo=5 if CC18_334A==3
{txt}(94 real changes made)

{com}. replace constolibideo=6 if CC18_334A==2
{txt}(140 real changes made)

{com}. replace constolibideo=7 if CC18_334A==1
{txt}(107 real changes made)

{com}. 
. gen right_ideology=.
{txt}(1,000 missing values generated)

{com}. replace right_ideology=1 if CC18_334A==1
{txt}(107 real changes made)

{com}. replace right_ideology=2 if CC18_334A==2
{txt}(140 real changes made)

{com}. replace right_ideology=3 if CC18_334A==3
{txt}(94 real changes made)

{com}. replace right_ideology=4 if CC18_334A==4
{txt}(235 real changes made)

{com}. replace right_ideology=5 if CC18_334A==5
{txt}(96 real changes made)

{com}. replace right_ideology=6 if CC18_334A==6
{txt}(163 real changes made)

{com}. replace right_ideology=7 if CC18_334A==7
{txt}(107 real changes made)

{com}. 
. gen dem_pid=0
{txt}
{com}. replace dem_pid=1 if pid3==1
{txt}(351 real changes made)

{com}. 
. gen rep_pid=0
{txt}
{com}. replace rep_pid=1 if pid3==2
{txt}(245 real changes made)

{com}. 
. gen ind_pid=0
{txt}
{com}. replace ind_pid=1 if pid3==3
{txt}(285 real changes made)

{com}. 
. gen pid7republican=pid7
{txt}
{com}. replace pid7republican=. if pid7==8
{txt}(44 real changes made, 44 to missing)

{com}. 
. * Table 6
. regress ProgTaxOrder EqualTreatExpos female somecollege college4degplus faminc2 black hisp othermin pid7republican [pweight=teamweight], robust
{txt}(sum of wgt is 822.4917617003438)

Linear regression                               Number of obs     = {res}       864
                                                {txt}F(9, 854)         =  {res}    15.08
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1549
                                                {txt}Root MSE          =    {res} .67996

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   ProgTaxOrder{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
EqualTreatExpos {c |}{col 17}{res}{space 2}-.1709486{col 29}{space 2}  .059498{col 40}{space 1}   -2.87{col 49}{space 3}0.004{col 57}{space 4} -.287728{col 70}{space 3}-.0541693
{txt}{space 9}female {c |}{col 17}{res}{space 2}  .060911{col 29}{space 2} .0642677{col 40}{space 1}    0.95{col 49}{space 3}0.344{col 57}{space 4}-.0652301{col 70}{space 3} .1870522
{txt}{space 4}somecollege {c |}{col 17}{res}{space 2} .0780759{col 29}{space 2} .0796077{col 40}{space 1}    0.98{col 49}{space 3}0.327{col 57}{space 4}-.0781737{col 70}{space 3} .2343255
{txt}college4degplus {c |}{col 17}{res}{space 2} .0835456{col 29}{space 2} .0724628{col 40}{space 1}    1.15{col 49}{space 3}0.249{col 57}{space 4}-.0586804{col 70}{space 3} .2257717
{txt}{space 8}faminc2 {c |}{col 17}{res}{space 2}-.0129274{col 29}{space 2} .0102015{col 40}{space 1}   -1.27{col 49}{space 3}0.205{col 57}{space 4}-.0329504{col 70}{space 3} .0070956
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0314724{col 29}{space 2} .1106036{col 40}{space 1}   -0.28{col 49}{space 3}0.776{col 57}{space 4}-.2485591{col 70}{space 3} .1856143
{txt}{space 11}hisp {c |}{col 17}{res}{space 2}-.0677924{col 29}{space 2}  .156609{col 40}{space 1}   -0.43{col 49}{space 3}0.665{col 57}{space 4} -.375176{col 70}{space 3} .2395912
{txt}{space 7}othermin {c |}{col 17}{res}{space 2}-.1752145{col 29}{space 2} .1177891{col 40}{space 1}   -1.49{col 49}{space 3}0.137{col 57}{space 4}-.4064046{col 70}{space 3} .0559756
{txt}{space 1}pid7republican {c |}{col 17}{res}{space 2}-.1200206{col 29}{space 2} .0142835{col 40}{space 1}   -8.40{col 49}{space 3}0.000{col 57}{space 4}-.1480555{col 70}{space 3}-.0919858
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.507224{col 29}{space 2} .1225774{col 40}{space 1}   20.45{col 49}{space 3}0.000{col 57}{space 4} 2.266636{col 70}{space 3} 2.747812
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. regress equal_treat EqualTreatExpos female somecollege college4degplus faminc2 black hisp othermin pid7republican [pweight=teamweight], robust
{txt}(sum of wgt is 804.0368705865557)

Linear regression                               Number of obs     = {res}       844
                                                {txt}F(9, 834)         =  {res}     4.07
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0520
                                                {txt}Root MSE          =    {res} 1.3874

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}    equal_treat{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
EqualTreatExpos {c |}{col 17}{res}{space 2} .2771493{col 29}{space 2} .1173216{col 40}{space 1}    2.36{col 49}{space 3}0.018{col 57}{space 4} .0468689{col 70}{space 3} .5074297
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.1497356{col 29}{space 2} .1223622{col 40}{space 1}   -1.22{col 49}{space 3}0.221{col 57}{space 4}-.3899096{col 70}{space 3} .0904384
{txt}{space 4}somecollege {c |}{col 17}{res}{space 2}-.1351278{col 29}{space 2} .1529319{col 40}{space 1}   -0.88{col 49}{space 3}0.377{col 57}{space 4}-.4353046{col 70}{space 3} .1650489
{txt}college4degplus {c |}{col 17}{res}{space 2}-.2510665{col 29}{space 2} .1480509{col 40}{space 1}   -1.70{col 49}{space 3}0.090{col 57}{space 4}-.5416627{col 70}{space 3} .0395296
{txt}{space 8}faminc2 {c |}{col 17}{res}{space 2} .0197578{col 29}{space 2} .0185385{col 40}{space 1}    1.07{col 49}{space 3}0.287{col 57}{space 4}-.0166299{col 70}{space 3} .0561454
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.2079202{col 29}{space 2} .2208756{col 40}{space 1}   -0.94{col 49}{space 3}0.347{col 57}{space 4}-.6414576{col 70}{space 3} .2256172
{txt}{space 11}hisp {c |}{col 17}{res}{space 2} .2442942{col 29}{space 2} .2615304{col 40}{space 1}    0.93{col 49}{space 3}0.351{col 57}{space 4}-.2690409{col 70}{space 3} .7576293
{txt}{space 7}othermin {c |}{col 17}{res}{space 2}-.0479449{col 29}{space 2} .2413512{col 40}{space 1}   -0.20{col 49}{space 3}0.843{col 57}{space 4} -.521672{col 70}{space 3} .4257822
{txt}{space 1}pid7republican {c |}{col 17}{res}{space 2} .0936866{col 29}{space 2} .0279268{col 40}{space 1}    3.35{col 49}{space 3}0.001{col 57}{space 4} .0388716{col 70}{space 3} .1485016
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.890466{col 29}{space 2} .2310823{col 40}{space 1}   12.51{col 49}{space 3}0.000{col 57}{space 4} 2.436895{col 70}{space 3} 3.344037
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. * Table 7
. regress ProgTaxOrder equal_treat female somecollege college4degplus faminc2 black hisp othermin pid7republican, robust

{txt}Linear regression                               Number of obs     = {res}       843
                                                {txt}F(9, 833)         =  {res}    28.32
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2132
                                                {txt}Root MSE          =    {res} .64374

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   ProgTaxOrder{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}equal_treat {c |}{col 17}{res}{space 2}-.1102149{col 29}{space 2} .0168432{col 40}{space 1}   -6.54{col 49}{space 3}0.000{col 57}{space 4} -.143275{col 70}{space 3}-.0771547
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0123053{col 29}{space 2}  .047592{col 40}{space 1}   -0.26{col 49}{space 3}0.796{col 57}{space 4}-.1057196{col 70}{space 3}  .081109
{txt}{space 4}somecollege {c |}{col 17}{res}{space 2} .1132231{col 29}{space 2}  .059445{col 40}{space 1}    1.90{col 49}{space 3}0.057{col 57}{space 4}-.0034565{col 70}{space 3} .2299027
{txt}college4degplus {c |}{col 17}{res}{space 2} .0665757{col 29}{space 2} .0581262{col 40}{space 1}    1.15{col 49}{space 3}0.252{col 57}{space 4}-.0475153{col 70}{space 3} .1806666
{txt}{space 8}faminc2 {c |}{col 17}{res}{space 2}-.0124606{col 29}{space 2} .0069023{col 40}{space 1}   -1.81{col 49}{space 3}0.071{col 57}{space 4}-.0260085{col 70}{space 3} .0010874
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0819481{col 29}{space 2} .0769795{col 40}{space 1}   -1.06{col 49}{space 3}0.287{col 57}{space 4}-.2330447{col 70}{space 3} .0691486
{txt}{space 11}hisp {c |}{col 17}{res}{space 2} .0175782{col 29}{space 2} .0867856{col 40}{space 1}    0.20{col 49}{space 3}0.840{col 57}{space 4} -.152766{col 70}{space 3} .1879223
{txt}{space 7}othermin {c |}{col 17}{res}{space 2}-.0143398{col 29}{space 2} .0861745{col 40}{space 1}   -0.17{col 49}{space 3}0.868{col 57}{space 4}-.1834845{col 70}{space 3} .1548048
{txt}{space 1}pid7republican {c |}{col 17}{res}{space 2} -.122326{col 29}{space 2} .0108754{col 40}{space 1}  -11.25{col 49}{space 3}0.000{col 57}{space 4}-.1436723{col 70}{space 3}-.1009796
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 2.817549{col 29}{space 2} .0963238{col 40}{space 1}   29.25{col 49}{space 3}0.000{col 57}{space 4} 2.628483{col 70}{space 3} 3.006615
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. ivreg2 ProgTaxOrder female somecollege college4degplus faminc2 black hisp othermin pid7republican (equal_treat=EqualTreatExpos), robust
{res}
{txt}IV (2SLS) estimation
{hline 20}

Estimates efficient for homoskedasticity only
Statistics robust to heteroskedasticity

{col 55}Number of obs = {res}     843
{txt}{col 55}F(  9,   833) = {res}   18.64
{txt}{col 55}Prob > F      = {res}  0.0000
{txt}Total (centered) SS     = {res} 438.7330961{txt}{col 55}Centered R2   = {res}  0.0367
{txt}Total (uncentered) SS   = {res}        3751{txt}{col 55}Uncentered R2 = {res}  0.8873
{txt}Residual SS             = {res} 422.6248526{txt}{col 55}Root MSE      = {res}    .708

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}   ProgTaxOrder{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      z{col 49}   P>|z|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}equal_treat {c |}{col 17}{res}{space 2}-.3285275{col 29}{space 2} .1381808{col 40}{space 1}   -2.38{col 49}{space 3}0.017{col 57}{space 4}-.5993569{col 70}{space 3}-.0576982
{txt}{space 9}female {c |}{col 17}{res}{space 2}-.0596271{col 29}{space 2} .0590886{col 40}{space 1}   -1.01{col 49}{space 3}0.313{col 57}{space 4}-.1754386{col 70}{space 3} .0561844
{txt}{space 4}somecollege {c |}{col 17}{res}{space 2} .0979227{col 29}{space 2} .0666365{col 40}{space 1}    1.47{col 49}{space 3}0.142{col 57}{space 4}-.0326824{col 70}{space 3} .2285279
{txt}college4degplus {c |}{col 17}{res}{space 2} .0026857{col 29}{space 2} .0780543{col 40}{space 1}    0.03{col 49}{space 3}0.973{col 57}{space 4}-.1502979{col 70}{space 3} .1556693
{txt}{space 8}faminc2 {c |}{col 17}{res}{space 2}-.0085829{col 29}{space 2} .0078762{col 40}{space 1}   -1.09{col 49}{space 3}0.276{col 57}{space 4}  -.02402{col 70}{space 3} .0068541
{txt}{space 10}black {c |}{col 17}{res}{space 2}-.0890902{col 29}{space 2} .0875729{col 40}{space 1}   -1.02{col 49}{space 3}0.309{col 57}{space 4}  -.26073{col 70}{space 3} .0825496
{txt}{space 11}hisp {c |}{col 17}{res}{space 2} .0388408{col 29}{space 2} .0981782{col 40}{space 1}    0.40{col 49}{space 3}0.692{col 57}{space 4} -.153585{col 70}{space 3} .2312665
{txt}{space 7}othermin {c |}{col 17}{res}{space 2}-.0012825{col 29}{space 2} .0964285{col 40}{space 1}   -0.01{col 49}{space 3}0.989{col 57}{space 4}-.1902789{col 70}{space 3}  .187714
{txt}{space 1}pid7republican {c |}{col 17}{res}{space 2}-.1020665{col 29}{space 2}  .018365{col 40}{space 1}   -5.56{col 49}{space 3}0.000{col 57}{space 4}-.1380612{col 70}{space 3}-.0660718
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} 3.485008{col 29}{space 2}  .428525{col 40}{space 1}    8.13{col 49}{space 3}0.000{col 57}{space 4} 2.645114{col 70}{space 3} 4.324901
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{help ivreg2##idtest:Underidentification test} (Kleibergen-Paap rk LM statistic):{res}{col 71}  13.547
{txt}{col 52}Chi-sq({res}1{txt}) P-val =  {res}{col 73}0.0002
{txt}{hline 78}
{help ivreg2##widtest:Weak identification test} (Cragg-Donald Wald F statistic):{res}{col 71}  13.652
{txt}                         (Kleibergen-Paap rk Wald F statistic):{res}{col 71}  13.606
{txt}Stock-Yogo weak ID test critical values:{res}{txt}{col 42}10% maximal IV size{res}{col 73} 16.38
{txt}{col 42}15% maximal IV size{res}{col 73}  8.96
{txt}{col 42}20% maximal IV size{res}{col 73}  6.66
{txt}{col 42}25% maximal IV size{res}{col 73}  5.53
{txt}Source: Stock-Yogo (2005).  Reproduced by permission.
NB: Critical values are for Cragg-Donald F statistic and i.i.d. errors.
{hline 78}
{help ivreg2##overidtests:Hansen J statistic} (overidentification test of all instruments):{res}{col 71}   0.000
{txt}{col 50}(equation exactly identified)
{hline 78}
Instrumented:{col 23}equal_treat
Included instruments:{col 23}female somecollege college4degplus faminc2 black hisp
{col 23}othermin pid7republican
Excluded instruments:{col 23}EqualTreatExpos
{hline 78}

{com}. 
. * Table A.3
. 
. sum female age1830 age3150 age5165 agegt65 college4degplus black hisp

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}female {c |}{res}      1,000        .574    .4947411          0          1
{txt}{space 5}age1830 {c |}{res}      1,000        .223    .4164666          0          1
{txt}{space 5}age3150 {c |}{res}      1,000        .308    .4618976          0          1
{txt}{space 5}age5165 {c |}{res}      1,000        .273    .4457238          0          1
{txt}{space 5}agegt65 {c |}{res}      1,000        .196    .3971671          0          1
{txt}{hline 13}{c +}{hline 57}
college4de~s {c |}{res}      1,000        .379    .4853809          0          1
{txt}{space 7}black {c |}{res}      1,000        .094    .2919747          0          1
{txt}{space 8}hisp {c |}{res}      1,000        .084    .2775266          0          1
{txt}
{com}. svyset caseid [pweight=teamweight]

      {txt}pweight:{col 16}{res}teamweight
          {txt}VCE:{col 16}{res}linearized
  {txt}Single unit:{col 16}{res}missing
     {txt}Strata 1:{col 16}<one>
         SU 1:{col 16}{res}caseid
        {txt}FPC 1:{col 16}<zero>
{p2colreset}{...}

{com}. svy: mean female age1830 age3150 age5165 agegt65 college4degplus black hisp
{res}{txt}(running {bf:mean} on estimation sample)
{res}
{txt}Survey: Mean estimation

{col 1}Number of strata{col 18}= {res}      1{txt}{col 38}Number of obs{col 54}= {res}     1,000
{txt}{col 1}Number of PSUs{col 18}= {res}  1,000{txt}{col 38}Population size{col 54}={res}      1,000
{txt}{col 38}Design df{col 54}= {res}       999

{txt}{hline 16}{c TT}{hline 11}{hline 11}{hline 14}{hline 12}
{col 17}{c |}{col 29}  Linearized
{col 17}{c |}       Mean{col 29}   Std. Err.{col 41}     [95% Con{col 54}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 14}{hline 12}
{space 9}female {c |}{col 17}{res}{space 2}  .514998{col 29}{space 2} .0206537{col 40}{space 5} .4744683{col 54}{space 3} .5555277
{txt}{space 8}age1830 {c |}{col 17}{res}{space 2} .2333439{col 29}{space 2} .0183709{col 40}{space 5}  .197294{col 54}{space 3} .2693938
{txt}{space 8}age3150 {c |}{col 17}{res}{space 2} .3044367{col 29}{space 2} .0186509{col 40}{space 5} .2678373{col 54}{space 3} .3410362
{txt}{space 8}age5165 {c |}{col 17}{res}{space 2}  .266796{col 29}{space 2}    .0178{col 40}{space 5} .2318663{col 54}{space 3} .3017256
{txt}{space 8}agegt65 {c |}{col 17}{res}{space 2} .1954234{col 29}{space 2} .0159918{col 40}{space 5} .1640421{col 54}{space 3} .2268047
{txt}college4degplus {c |}{col 17}{res}{space 2} .2988967{col 29}{space 2} .0171611{col 40}{space 5} .2652206{col 54}{space 3} .3325727
{txt}{space 10}black {c |}{col 17}{res}{space 2}   .12558{col 29}{space 2} .0163107{col 40}{space 5} .0935728{col 54}{space 3} .1575872
{txt}{space 11}hisp {c |}{col 17}{res}{space 2} .0869191{col 29}{space 2} .0134067{col 40}{space 5} .0606106{col 54}{space 3} .1132276
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 14}{hline 12}

{com}. 
. clear all
{res}{txt}
{com}. 
. /**
> UK Pilot Survey Analysis: Table A.4; Table A.5
> **/
. 
. use "Brexit pilot (with IPW and context data).dta", clear
{txt}( )

{com}. 
. /****
> Variable and global variable construction
> *****/
. 
. rename Q15 taxUnder10k
{res}{txt}
{com}. rename Q16 tax10_45k
{res}{txt}
{com}. rename Q17 tax45_150k
{res}{txt}
{com}. rename Q18 taxOver150k
{res}{txt}
{com}. gen linearTaxOver150k = .
{txt}(1,000 missing values generated)

{com}. replace linearTax = 0 if taxOver150k == 1
{txt}(6 real changes made)

{com}. replace linearTax = 5 if taxOver150k == 2
{txt}(10 real changes made)

{com}. replace linearTax = 10 if taxOver150k == 3
{txt}(9 real changes made)

{com}. replace linearTax = 15 if taxOver150k == 4
{txt}(18 real changes made)

{com}. replace linearTax = 20 if taxOver150k == 5
{txt}(43 real changes made)

{com}. replace linearTax = 25 if taxOver150k == 6
{txt}(39 real changes made)

{com}. replace linearTax = 30 if taxOver150k == 7
{txt}(55 real changes made)

{com}. replace linearTax = 35 if taxOver150k == 8
{txt}(59 real changes made)

{com}. replace linearTax = 40 if taxOver150k == 9
{txt}(205 real changes made)

{com}. replace linearTax = 50 if taxOver150k == 10
{txt}(325 real changes made)

{com}. replace linearTax = 60 if taxOver150k == 11
{txt}(176 real changes made)

{com}. replace linearTax = 70 if taxOver150k == 12
{txt}(32 real changes made)

{com}. replace linearTax = 80 if taxOver150k == 13
{txt}(23 real changes made)

{com}. 
. gen statusquo_prompt=q15_18Rand
{txt}
{com}. 
. rename Q31 equal_treat
{res}{txt}
{com}. label variable equal_treat "Should government treat citizens equally?"
{txt}
{com}. recode equal_treat 1=5 2=4 3=3 4=2 5=1
{txt}(equal_treat: 738 changes made)

{com}. label define equal_treat_lbl    1 "Treat citizens differently" ///
>                                                                         2 "2" ///
>                                                                         3 "3" ///
>                                                                         4 "4" ///
>                                                                         5 "Treat citizens equally", replace
{txt}
{com}. label values equal_treat equal_treat_lbl
{txt}
{com}. 
. gen treatEqualdi = cond(equal_treat >= 3, 1, 0)
{txt}
{com}. 
. rename Q39 right_ideology
{res}{txt}
{com}. label variable right_ideology "Ideological self-identification"
{txt}
{com}. label define ideology_lbl       1 "Left" ///
>                                                                 2 "2" ///
>                                                                 3 "3" ///
>                                                                 4 "4" ///
>                                                                 5 "5" ///
>                                                                 6 "6" ///
>                                                                 7 "7" ///
>                                                                 8 "8" ///
>                                                                 9 "9" ///
>                                                                 10 "10" ///
>                                                                 11 "Right", replace
{txt}
{com}. label values right_ideology ideology_lbl
{txt}
{com}. 
. rename Q33 work_luck
{res}{txt}
{com}. label variable work_luck "Work hard or lucky to get ahead?"
{txt}
{com}. label define work_luck_lbl 1 "Hard work is most important" ///
>         2 "Hard work & luck are equally important" ///
>         3 "Luck is the most important", replace
{txt}
{com}. label values work_luck work_luck_lbl
{txt}
{com}. 
. gen hardwork=1 if work_luck==1
{txt}(717 missing values generated)

{com}. replace hardwork=0 if work_luck==2|work_luck==3
{txt}(717 real changes made)

{com}. 
. gen reduceIneq = .
{txt}(1,000 missing values generated)

{com}. replace reduceIneq = 1 if Q49 == 2 & Q50 == 1
{txt}(7 real changes made)

{com}. replace reduceIneq = 2 if Q49 == 2 & Q50 == 2
{txt}(32 real changes made)

{com}. replace reduceIneq = 3 if Q49 == 2 & Q50 == 3
{txt}(8 real changes made)

{com}. replace reduceIneq = 4 if Q49 == 3
{txt}(272 real changes made)

{com}. replace reduceIneq = 5 if Q49 == 1 & Q50 == 3
{txt}(62 real changes made)

{com}. replace reduceIneq = 6 if Q49 == 1 & Q50 == 2
{txt}(307 real changes made)

{com}. replace reduceIneq = 7 if Q49 == 1 & Q50 == 1
{txt}(312 real changes made)

{com}. gen ineqAverse = cond(reduceIneq > 4, 1, 0) if reduceIneq != .
{txt}
{com}. 
. rename Q47 govtsvcs
{res}{txt}
{com}. label variable govtsvcs "Should the government provide more, fewer, or the same # of services as it does now?"
{txt}note: label truncated to 80 characters

{com}. label define more_fewer_same_lbl 1 "More" 2 "Fewer" 3 "Same", replace
{txt}
{com}. label values govtsvcs more_fewer_same_lbl
{txt}
{com}. 
. rename Q48 govtsvcs_preflvl
{res}{txt}
{com}. label variable govtsvcs_preflvl "If govt should provide more/fewer services, how much?"
{txt}
{com}. label define scale_lot_slightly 1 "A lot" 2 "Somewhat" 3 "Slightly", replace
{txt}
{com}. label values govtsvcs_preflvl scale_lot_slightly
{txt}
{com}. 
. gen moregovtservices7=.
{txt}(1,000 missing values generated)

{com}. replace moregovtservices7=1 if govtsvcs==2 & govtsvcs_preflvl==1
{txt}(8 real changes made)

{com}. replace moregovtservices7=2 if govtsvcs==2 & govtsvcs_preflvl==2
{txt}(40 real changes made)

{com}. replace moregovtservices7=3 if govtsvcs==2 & govtsvcs_preflvl==3
{txt}(36 real changes made)

{com}. replace moregovtservices7=4 if govtsvcs==3
{txt}(396 real changes made)

{com}. replace moregovtservices7=5 if govtsvcs==1 & govtsvcs_preflvl==3
{txt}(65 real changes made)

{com}. replace moregovtservices7=6 if govtsvcs==1 & govtsvcs_preflvl==2
{txt}(293 real changes made)

{com}. replace moregovtservices7=7 if govtsvcs==1 & govtsvcs_preflvl==1
{txt}(162 real changes made)

{com}. label variable moregovtservices7 "Should the government provide more, fewer, or the same # of services as it does now?"
{txt}note: label truncated to 80 characters

{com}. label define moregovtservices7_lbl 1 "A lot fewer" 2 "somewhat fewer" 3 "slighter fewer" 4 "same" 5 "slightly more" 6 "somewhat more" 7 "a lot more", replace
{txt}
{com}. label values moregovtservices7 moregovtservices7_lbl
{txt}
{com}. 
. gen cons_id=0
{txt}
{com}. replace cons_id=1 if partyPref==1
{txt}(206 real changes made)

{com}. 
. gen lab_id=0
{txt}
{com}. replace lab_id=1 if partyPref==2
{txt}(176 real changes made)

{com}. 
. gen age1830=0
{txt}
{com}. replace age1830=1 if age>=18 & age<=30
{txt}(219 real changes made)

{com}. gen age3150=0
{txt}
{com}. replace age3150=1 if age>=31 & age<=50
{txt}(336 real changes made)

{com}. gen age5165=0
{txt}
{com}. replace age5165=1 if age>=51 & age<=65
{txt}(244 real changes made)

{com}. gen agegt65=0
{txt}
{com}. replace agegt65=1 if age>65
{txt}(201 real changes made)

{com}. 
. * Table A.4
. 
. tab equal_treat

   {txt}Should government treat {c |}
         citizens equally? {c |}      Freq.     Percent        Cum.
{hline 27}{c +}{hline 35}
Treat citizens differently {c |}{res}        146       14.60       14.60
{txt}                         2 {c |}{res}        299       29.90       44.50
{txt}                         3 {c |}{res}        262       26.20       70.70
{txt}                         4 {c |}{res}        129       12.90       83.60
{txt}    Treat citizens equally {c |}{res}        164       16.40      100.00
{txt}{hline 27}{c +}{hline 35}
                     Total {c |}{res}      1,000      100.00
{txt}
{com}. 
. * Table A.5
. 
. reg linearTaxOver150k equal_treat statusquo_prompt [pweight=weight], robust
{txt}(sum of wgt is 999.9999999999984)

Linear regression                               Number of obs     = {res}     1,000
                                                {txt}F(2, 997)         =  {res}    11.53
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.0295
                                                {txt}Root MSE          =    {res} 15.278

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}linearTaxOv~150k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}equal_treat {c |}{col 18}{res}{space 2}-.9043541{col 30}{space 2} .4993438{col 41}{space 1}   -1.81{col 50}{space 3}0.070{col 58}{space 4} -1.88424{col 71}{space 3} .0755314
{txt}statusquo_prompt {c |}{col 18}{res}{space 2} 4.802721{col 30}{space 2} 1.192994{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4} 2.461653{col 71}{space 3} 7.143789
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 45.05294{col 30}{space 2} 1.623128{col 41}{space 1}   27.76{col 50}{space 3}0.000{col 58}{space 4}  41.8678{col 71}{space 3} 48.23808
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc statusquo_prompt [pweight=weight], robust
{txt}(sum of wgt is 709.3185656170853)

Linear regression                               Number of obs     = {res}       731
                                                {txt}F(8, 722)         =  {res}     9.28
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1074
                                                {txt}Root MSE          =    {res} 14.075

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}linearTaxOv~150k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}equal_treat {c |}{col 18}{res}{space 2}-1.253255{col 30}{space 2} .4732593{col 41}{space 1}   -2.65{col 50}{space 3}0.008{col 58}{space 4}-2.182384{col 71}{space 3}-.3241267
{txt}{space 10}female {c |}{col 18}{res}{space 2}-2.066642{col 30}{space 2} 1.220374{col 41}{space 1}   -1.69{col 50}{space 3}0.091{col 58}{space 4}-4.462546{col 71}{space 3}  .329263
{txt}{space 9}age3150 {c |}{col 18}{res}{space 2} 2.135726{col 30}{space 2}  1.93608{col 41}{space 1}    1.10{col 50}{space 3}0.270{col 58}{space 4}-1.665294{col 71}{space 3} 5.936746
{txt}{space 9}age5165 {c |}{col 18}{res}{space 2} 4.520094{col 30}{space 2} 1.957725{col 41}{space 1}    2.31{col 50}{space 3}0.021{col 58}{space 4} .6765796{col 71}{space 3} 8.363608
{txt}{space 9}agegt65 {c |}{col 18}{res}{space 2}   6.0556{col 30}{space 2} 2.039918{col 41}{space 1}    2.97{col 50}{space 3}0.003{col 58}{space 4} 2.050722{col 71}{space 3} 10.06048
{txt}{space 2}universityEduc {c |}{col 18}{res}{space 2} 4.512862{col 30}{space 2} 1.315401{col 41}{space 1}    3.43{col 50}{space 3}0.001{col 58}{space 4} 1.930394{col 71}{space 3}  7.09533
{txt}{space 10}hh_inc {c |}{col 18}{res}{space 2} .4736075{col 30}{space 2} .1786617{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4}  .122849{col 71}{space 3} .8243659
{txt}statusquo_prompt {c |}{col 18}{res}{space 2} 4.813491{col 30}{space 2} 1.195824{col 41}{space 1}    4.03{col 50}{space 3}0.000{col 58}{space 4} 2.465784{col 71}{space 3} 7.161199
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 39.06657{col 30}{space 2} 2.662102{col 41}{space 1}   14.68{col 50}{space 3}0.000{col 58}{space 4} 33.84018{col 71}{space 3} 44.29295
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  right_ideology statusquo_prompt [pweight=weight], robust
{txt}(sum of wgt is 709.3185656170853)

Linear regression                               Number of obs     = {res}       731
                                                {txt}F(9, 721)         =  {res}    10.42
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1424
                                                {txt}Root MSE          =    {res} 13.805

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}linearTaxOv~150k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}equal_treat {c |}{col 18}{res}{space 2}-1.206469{col 30}{space 2} .4528077{col 41}{space 1}   -2.66{col 50}{space 3}0.008{col 58}{space 4}-2.095448{col 71}{space 3}-.3174899
{txt}{space 10}female {c |}{col 18}{res}{space 2} -2.48049{col 30}{space 2} 1.185366{col 41}{space 1}   -2.09{col 50}{space 3}0.037{col 58}{space 4}-4.807671{col 71}{space 3}-.1533097
{txt}{space 9}age3150 {c |}{col 18}{res}{space 2} 2.333807{col 30}{space 2} 1.882411{col 41}{space 1}    1.24{col 50}{space 3}0.215{col 58}{space 4}-1.361856{col 71}{space 3} 6.029469
{txt}{space 9}age5165 {c |}{col 18}{res}{space 2}  4.72878{col 30}{space 2} 1.905568{col 41}{space 1}    2.48{col 50}{space 3}0.013{col 58}{space 4}  .987655{col 71}{space 3} 8.469906
{txt}{space 9}agegt65 {c |}{col 18}{res}{space 2}  7.71792{col 30}{space 2} 2.041754{col 41}{space 1}    3.78{col 50}{space 3}0.000{col 58}{space 4} 3.709426{col 71}{space 3} 11.72641
{txt}{space 2}universityEduc {c |}{col 18}{res}{space 2} 3.987668{col 30}{space 2}  1.27533{col 41}{space 1}    3.13{col 50}{space 3}0.002{col 58}{space 4} 1.483863{col 71}{space 3} 6.491472
{txt}{space 10}hh_inc {c |}{col 18}{res}{space 2} .4421251{col 30}{space 2} .1711103{col 41}{space 1}    2.58{col 50}{space 3}0.010{col 58}{space 4} .1061911{col 71}{space 3} .7780591
{txt}{space 2}right_ideology {c |}{col 18}{res}{space 2}-1.411944{col 30}{space 2} .2876138{col 41}{space 1}   -4.91{col 50}{space 3}0.000{col 58}{space 4}-1.976604{col 71}{space 3}-.8472832
{txt}statusquo_prompt {c |}{col 18}{res}{space 2} 4.850582{col 30}{space 2} 1.166165{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} 2.561097{col 71}{space 3} 7.140067
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 45.93941{col 30}{space 2} 2.709231{col 41}{space 1}   16.96{col 50}{space 3}0.000{col 58}{space 4} 40.62049{col 71}{space 3} 51.25833
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  cons_id statusquo_prompt [pweight=weight], robust
{txt}(sum of wgt is 709.3185656170853)

Linear regression                               Number of obs     = {res}       731
                                                {txt}F(9, 721)         =  {res}     8.47
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1099
                                                {txt}Root MSE          =    {res} 14.064

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}linearTaxOv~150k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}equal_treat {c |}{col 18}{res}{space 2}-1.240302{col 30}{space 2}  .472093{col 41}{space 1}   -2.63{col 50}{space 3}0.009{col 58}{space 4}-2.167143{col 71}{space 3}-.3134607
{txt}{space 10}female {c |}{col 18}{res}{space 2} -2.19179{col 30}{space 2} 1.233432{col 41}{space 1}   -1.78{col 50}{space 3}0.076{col 58}{space 4}-4.613338{col 71}{space 3}  .229758
{txt}{space 9}age3150 {c |}{col 18}{res}{space 2} 2.236501{col 30}{space 2} 1.929657{col 41}{space 1}    1.16{col 50}{space 3}0.247{col 58}{space 4}-1.551917{col 71}{space 3} 6.024919
{txt}{space 9}age5165 {c |}{col 18}{res}{space 2} 4.761811{col 30}{space 2} 1.953679{col 41}{space 1}    2.44{col 50}{space 3}0.015{col 58}{space 4} .9262314{col 71}{space 3} 8.597392
{txt}{space 9}agegt65 {c |}{col 18}{res}{space 2} 6.744261{col 30}{space 2} 2.080469{col 41}{space 1}    3.24{col 50}{space 3}0.001{col 58}{space 4} 2.659759{col 71}{space 3} 10.82876
{txt}{space 2}universityEduc {c |}{col 18}{res}{space 2} 4.533328{col 30}{space 2} 1.316119{col 41}{space 1}    3.44{col 50}{space 3}0.001{col 58}{space 4} 1.949444{col 71}{space 3} 7.117212
{txt}{space 10}hh_inc {c |}{col 18}{res}{space 2} .5008697{col 30}{space 2} .1785536{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .1503226{col 71}{space 3} .8514168
{txt}{space 9}cons_id {c |}{col 18}{res}{space 2}-1.962556{col 30}{space 2} 1.484647{col 41}{space 1}   -1.32{col 50}{space 3}0.187{col 58}{space 4}-4.877303{col 71}{space 3} .9521907
{txt}statusquo_prompt {c |}{col 18}{res}{space 2} 4.924327{col 30}{space 2}  1.20466{col 41}{space 1}    4.09{col 50}{space 3}0.000{col 58}{space 4} 2.559268{col 71}{space 3} 7.289387
{txt}{space 11}_cons {c |}{col 18}{res}{space 2}  39.0151{col 30}{space 2} 2.661288{col 41}{space 1}   14.66{col 50}{space 3}0.000{col 58}{space 4}  33.7903{col 71}{space 3}  44.2399
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  hardwork statusquo_prompt [pweight=weight], robust
{txt}(sum of wgt is 709.3185656170853)

Linear regression                               Number of obs     = {res}       731
                                                {txt}F(9, 721)         =  {res}     8.60
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1114
                                                {txt}Root MSE          =    {res} 14.053

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}linearTaxOv~150k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}equal_treat {c |}{col 18}{res}{space 2}-1.202028{col 30}{space 2} .4759425{col 41}{space 1}   -2.53{col 50}{space 3}0.012{col 58}{space 4}-2.136427{col 71}{space 3}-.2676291
{txt}{space 10}female {c |}{col 18}{res}{space 2}-2.134587{col 30}{space 2} 1.215355{col 41}{space 1}   -1.76{col 50}{space 3}0.079{col 58}{space 4}-4.520645{col 71}{space 3} .2514712
{txt}{space 9}age3150 {c |}{col 18}{res}{space 2} 1.952193{col 30}{space 2} 1.907007{col 41}{space 1}    1.02{col 50}{space 3}0.306{col 58}{space 4}-1.791757{col 71}{space 3} 5.696144
{txt}{space 9}age5165 {c |}{col 18}{res}{space 2}  4.21759{col 30}{space 2} 1.919174{col 41}{space 1}    2.20{col 50}{space 3}0.028{col 58}{space 4} .4497538{col 71}{space 3} 7.985426
{txt}{space 9}agegt65 {c |}{col 18}{res}{space 2} 5.969207{col 30}{space 2} 2.024261{col 41}{space 1}    2.95{col 50}{space 3}0.003{col 58}{space 4} 1.995057{col 71}{space 3} 9.943357
{txt}{space 2}universityEduc {c |}{col 18}{res}{space 2} 4.334573{col 30}{space 2}  1.30033{col 41}{space 1}    3.33{col 50}{space 3}0.001{col 58}{space 4} 1.781688{col 71}{space 3} 6.887458
{txt}{space 10}hh_inc {c |}{col 18}{res}{space 2} .4901993{col 30}{space 2} .1765367{col 41}{space 1}    2.78{col 50}{space 3}0.006{col 58}{space 4} .1436119{col 71}{space 3} .8367867
{txt}{space 8}hardwork {c |}{col 18}{res}{space 2}-2.101717{col 30}{space 2} 1.420275{col 41}{space 1}   -1.48{col 50}{space 3}0.139{col 58}{space 4}-4.890086{col 71}{space 3} .6866518
{txt}statusquo_prompt {c |}{col 18}{res}{space 2} 4.717991{col 30}{space 2} 1.193388{col 41}{space 1}    3.95{col 50}{space 3}0.000{col 58}{space 4} 2.375061{col 71}{space 3} 7.060921
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 39.73539{col 30}{space 2} 2.589259{col 41}{space 1}   15.35{col 50}{space 3}0.000{col 58}{space 4}   34.652{col 71}{space 3} 44.81878
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. reg linearTaxOver150k equal_treat female age3150 age5165 agegt65 universityEduc hh_inc  reduceIneq statusquo_prompt [pweight=weight], robust
{txt}(sum of wgt is 709.3185656170853)

Linear regression                               Number of obs     = {res}       731
                                                {txt}F(9, 721)         =  {res}    12.19
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.1838
                                                {txt}Root MSE          =    {res} 13.468

{txt}{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}linearTaxOv~150k{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}equal_treat {c |}{col 18}{res}{space 2}-.9294629{col 30}{space 2} .4444193{col 41}{space 1}   -2.09{col 50}{space 3}0.037{col 58}{space 4}-1.801973{col 71}{space 3}-.0569524
{txt}{space 10}female {c |}{col 18}{res}{space 2}-2.259176{col 30}{space 2} 1.138354{col 41}{space 1}   -1.98{col 50}{space 3}0.048{col 58}{space 4}-4.494061{col 71}{space 3}-.0242912
{txt}{space 9}age3150 {c |}{col 18}{res}{space 2} 1.987378{col 30}{space 2} 1.817681{col 41}{space 1}    1.09{col 50}{space 3}0.275{col 58}{space 4}-1.581202{col 71}{space 3} 5.555957
{txt}{space 9}age5165 {c |}{col 18}{res}{space 2} 3.977766{col 30}{space 2} 1.887671{col 41}{space 1}    2.11{col 50}{space 3}0.035{col 58}{space 4} .2717773{col 71}{space 3} 7.683755
{txt}{space 9}agegt65 {c |}{col 18}{res}{space 2}  6.27974{col 30}{space 2}  1.98505{col 41}{space 1}    3.16{col 50}{space 3}0.002{col 58}{space 4} 2.382572{col 71}{space 3} 10.17691
{txt}{space 2}universityEduc {c |}{col 18}{res}{space 2} 4.314286{col 30}{space 2} 1.217459{col 41}{space 1}    3.54{col 50}{space 3}0.000{col 58}{space 4} 1.924098{col 71}{space 3} 6.704473
{txt}{space 10}hh_inc {c |}{col 18}{res}{space 2} .5486561{col 30}{space 2} .1626704{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4} .2292919{col 71}{space 3} .8680203
{txt}{space 6}reduceIneq {c |}{col 18}{res}{space 2} 2.834666{col 30}{space 2} .4595427{col 41}{space 1}    6.17{col 50}{space 3}0.000{col 58}{space 4} 1.932465{col 71}{space 3} 3.736868
{txt}statusquo_prompt {c |}{col 18}{res}{space 2} 4.640664{col 30}{space 2} 1.136371{col 41}{space 1}    4.08{col 50}{space 3}0.000{col 58}{space 4} 2.409673{col 71}{space 3} 6.871654
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} 22.53057{col 30}{space 2} 3.929147{col 41}{space 1}    5.73{col 50}{space 3}0.000{col 58}{space 4} 14.81663{col 71}{space 3} 30.24451
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\ks298\Dropbox\FairnessSurvey\Data\Replication\SS_CPS_2021_Replication.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}18 Jan 2021, 14:13:00
{txt}{.-}
{smcl}
{txt}{sf}{ul off}